Abstract: The main purpose of this study was to investigate students’ academic performance (SAP) before, during, and after the COVID-19 pandemic in face-to-face (F2F) and online learning (OL) instructions. The study also attempted to determine the impact of gender and academic major on students’ academic performance. For the results of semester grade point average (SGPA), the findings of the study showed better SAP in F2F learning as compared to OL learning, while the results of grade point average (GPA) indicated better SAP in OL learning than in F2F learning. The findings supported the stated hypotheses by indicating the positive impact of gender and academic major on SAP in F2F and OL learning, before, during, and after the COVID-19 pandemic. The regression analysis revealed that the demographic variables can predict up to 18% variations in the student’s academic performance. These findings offer valuable insights for practical strategies to improve SAP in F2F and OL learning.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study conducts a comprehensive literature review to understand the direction and trends in contemporary labor studies, emphasizing significant global issues attracting scientific attention. Employing a scientometric approach, recent research data is explored using bibliometric analysis. The research adopts a mixed-methods approach, utilizing National Labor Statistics and conducting Focus Group Discussions (FGD) for nuanced insights into labor conditions in Indonesia. A bibliometric analysis of Scientific Labor Research Articles in Scopus (2020-2022) identifies trends and classifies global labor-related topics. Results highlight challenges in the labor landscape, driven by technological advancements and globalization, impacting job security, creating skill gaps, and raising concerns about the Fourth Industrial Revolution. The informal sector, particularly pronounced in Indonesia, poses challenges related to poverty, inequality, and the gig economy. Emerging issues like informal care for the elderly, social capital, and informal learning call for nuanced policy approaches. Indonesia's aging population adds complexity, requiring sustainable support mechanisms for healthcare and social services. The digital landscape, specifically Fintech, plays a significant role, yet research gaps persist. Bridging the digital talent gap is crucial for effective digital transformation, necessitating collaboration between government, educational institutions, and industry players. Challenges in Fintech development highlight the importance of initiatives promoting digital literacy, ethical practices, and regulatory frameworks. In conclusion, a holistic and collaborative approach is essential for navigating complexities and fostering sustainable economic growth.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Deep learning techniques are making significant contributions to the rapid advancements in forecasting. A standout algorithm known for its ability to produce accurate forecasts by recognizing temporal autocorrelation within the data is the Long Short-Term Memory (LSTM) algorithm, a component of Recurrent Neural Networks (RNN). The LSTM method employs both stateless and stateful architecture approaches, providing versatility in its application. This research aims to compare stateful and stateless algorithms in LSTM models, focusing on forecasting stock prices, such as those of Apple Inc. This comparative analysis is crucial, taking into account various characteristics of time series data, including the benefits and drawbacks of temporal autocorrelation. The comparison results reveal that, despite the stateful algorithm requiring more computational time, it achieves greater accuracy than the stateless approach. The forecast indicates a potential upward trend in share prices for the period of January to December 2024, according to the projected outlook for Apple's stock value. However, it is essential to exercise prudence in interpreting these results, considering that share price fluctuations are influenced by a significant number of variables.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: As the workforce worldwide goes through a transformative shift towards remote work, this paper discusses the positive effects of this quite flexible work arrangement on team’s innovation performance (TIP) in multinational, non-governmental organizations (NGOs). Adopting cross-sectional, quantitative research design, empirical data were collected through a survey of 268 employees of multinational NGOs operating in Jordan. The collected data were, then, analyzed using structural equation modeling. The results of the analysis showed that remote work has significant, positive effects on TIP in NGOs. Of the various remote work features investigated, spatial flexibility has the highest effect. The study results contribute to the ongoing discourse on the future of the work styles and have implications for leaders, policymakers, and practitioners who seek promoting innovation in multinational NGOs.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: With the increasing prevalence of network intrusions, the development of effective network intrusion detection systems (NIDS) has become crucial. In this study, we propose a novel NIDS approach that combines the power of long short-term memory (LSTM) and attention mechanisms to analyze the spatial and temporal features of network traffic data. We utilize the benchmark UNSW-NB15 dataset, which exhibits a diverse distribution of patterns, including a significant disparity in the size of the training and testing sets. Unlike traditional machine learning techniques like support vector machines (SVM) and k-nearest neighbors (KNN) that often struggle with limited feature sets and lower accuracy, our proposed model overcomes these limitations. Notably, existing models applied to this dataset typically require manual feature selection and extraction, which can be time-consuming and less precise. In contrast, our model achieves superior results in binary classification by leveraging the advantages of LSTM and attention mechanisms. Through extensive experiments and evaluations with state-of-the-art ML/DL models, we demonstrate the effectiveness and superiority of our proposed approach. Our findings highlight the potential of combining LSTM and attention mechanisms for enhanced network intrusion detection.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research is to examine the role of management of foreign direct investment and control of corruption in economic growth. The research data were collected from the ASEAN-6 countries including Indonesia, Malaysia, Thailand, Singapore, Philippines, and Vietnam during the period of 2002-2021. The research utilizes the panel vector autoregressive (PVAR) method developed by Abrrigo and Love (2015) [Abrigo, M. R. M., & Love, I. (2016). Estimation of panel vector autoregression in Stata.] to estimate the research model. The estimation results show that foreign direct investment and corruption control play an important role in promoting economic growth in the ASEAN-6 countries. Furthermore, foreign direct investment and corruption control are closely related to each other, indicating that economic growth is not only directly affected by foreign direct investment and corruption control but also indirectly influenced by each of these factors. This is a new finding of this research compared to previous studies. These findings provide significant empirical evidence for the ASEAN-6 countries, particularly in managing foreign direct investment and controlling corruption to promote economic growth. The implication of these results is that these countries identify appropriate policies to manage FDI and corruption control in order to maximize the level of economic growth.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Ransomware has evolved into a pervasive and extremely disruptive cybersecurity threat, causing substantial operational and financial damage to individuals and businesses. This article explores the critical domain of Ransomware detection and employs Machine Learning (ML) classifiers, particularly Decision Tree (DT), for Ransomware detection. The article also delves into the usefulness of DT in identifying Ransomware attacks, leveraging the innate ability of DT to recognize complex patterns within datasets. Instead of merely introducing DT as a detection method, we adopt a comprehensive approach, emphasizing the importance of fine-tuning DT hyperparameters. The optimization of these parameters is essential for maximizing the DT capability to identify Ransomware threats accurately. The obfuscated-MalMem2022 dataset, which is well-known for its extensive and challenging Ransomware-related data, was utilized to evaluate the effectiveness of DT in detecting Ransomware. The implementation uses the versatile Python programming language, renowned for its efficiency and adaptability in data analysis and ML tasks. Notably, the DT classifier consistently outperforms other classifiers in Ransomware detection, including K-Nearest Neighbors, Gradient Boosting Tree, Naive Bayes, and Linear Support Vector Classifier. For instance, the DT demonstrated exceptional effectiveness in distinguishing between Ransomware and benign data, as evidenced by its remarkable accuracy of 99.97%.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Rising sea surface height is one of the world's vital issues in marine ecosystems because it greatly affects the ecosystems as well as the socio-economic life of the surrounding environment. Pekalongan is one area in Indonesia facing the effects of this phenomenon. This problem deserves to be explored further with complex approaches. One of them is a neural network to perform forecasting more accurately. In neural networks, the time series approach can be used with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). By adding the bidirectional method to each of these two approaches, we will find the best method to use to perform the analysis. The best results were obtained by forecasting for 960 days using Vanilla BiGRU. The results can be interpreted from multiple perspectives. The forecasting results showed a fluctuating pattern as in previous periods, so it can be said that the pattern is still quite normal, which indicates that the terminal can continue to operate normally. However, the forecasting results from this study are expected to be a reference for information for the government to prevent future dangers.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: While many small and medium enterprises (SMEs)recognize the benefits of Big Data Analytics (BDA) for digital transformation, they face challenges in implementing this technology, highlighting the need for more research on its adoption by SMEs. The objective of this study is to amalgamate the Technology Organization Environment (TOE) framework with the Diffusion of Innovation (DOI) theory, aiming to dissect the factors that sway BDA adoption in Jordanian SMEs. Additionally, the study delves into how perceived usefulness impacts this adoption process. Utilizing structural equation modeling, the study examined data from 388 managers in Jordan. The study validates all its hypotheses, revealing that variables like relative advantage, compatibility, complexity, top management support, competitive pressure, and security influence perceived usefulness, which subsequently has a positive impact on BDA adoption. This research presents a range of theoretical and practical insights.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Responsive, timely, and friendly service quality plays a central role in shaping trust between the government and citizens. With the improvement of service quality, the public feels valued and heard, reinforcing the mutual trust relationship between the government and citizens. In this regard, technology-enabled service processes can streamline time and cost, while automation reduces the risk of human errors. Through web platforms or applications, the government can provide easier access for citizens to various services without the need to physically visit government offices. Good and quality public services are not only aimed at meeting the practical needs of the public but also play a role in shaping the mutual trust relationship between the government and citizens. Therefore, the concept of e-service quality, which encompasses the quality of services provided through electronic platforms, becomes crucial. The objective of this research is to explore the extent to which e-service quality can influence the level of public satisfaction. The research method employs a quantitative approach using primary data sources, where random sampling is applied as the sampling technique. The research respondents are citizens using digital public service platforms organized by the local government of Jakarta. The sample size used in this study is 262. The variables tested in this research involve e-service quality, public trust, and public satisfaction. In analyzing the data, this research utilizes SmartPLS 4 software. The analysis results show that e-service quality has a significant influence on the formation of public trust. Furthermore, findings indicate that e-service quality also significantly affects public satisfaction. However, the analysis results do not support the idea that public trust mediates the relationship between e-service quality and public satisfaction. This signifies that while public trust directly contributes to public satisfaction with public services, other unmeasured factors also play a role in shaping public perceptions and satisfaction.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The space-time model combines spatial and temporal elements. One example is the Generalized Space-Time Autoregressive (GSTAR) Model, which improves the Space-Time Autoregressive (STAR) model. The GSTAR model assumes that each location has heterogeneity characteristics, and that the data is stationary. In this research, the moving average component is calculated by involving the relationship between variable values at a certain time and residual values at a previous time, and it is assumed that the data is not stationary, so the model used is the Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) Model. The model order for GSTARIMA is determined through the Space-Time Autocorrelation Function (STACF) and Space-Time Partial Autocorrelation Function (STPACF) to ensure accurate forecasting. Previous research only discussed the GSTARIMA(1,1,1) model, so in this research, the GSTARIMA(3,1,1) model will be addressed as a form of development of the GSTARIMA(1,1,1) model and applied to climate data. The climate data used in this research is sourced from NASA POWER and consists of rainfall variables with large data sizes, requiring the use of the data analytics lifecycle method to analyse Big Data. The lifecycle includes six phases: discovery, data preparation, model planning, model building, communicating results, and operationalization. Based on the data processing results with Python software, the GSTARIMA(3,1,1) model has a MAPE value of 9% for out-sample data and 11% for in-sample data. In contrast, the GSTARIMA(1,1,1) model has a MAPE value of 11% for out-sample data and 12% for in-sample data. So the GSTARIMA(3,1,1) model provides more accurate forecasting results. Therefore, selecting the correct model order is crucial for accurate forecasting.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study conducts a quantitative inquiry into how components of gamification and customization are being used in Saudi Arabia's educational system. In our investigation, we zero in on how these factors could contribute to skill development. This investigation uses a thorough and rigorous quantitative research approach to probe students' preferences for gamification components and their thoughts on customization. The findings highlight the amazing congruence between people's preference for gamification components like points and badges and the need for adaptation and feedback in optimizing the effectiveness of the educational process. Through careful component analysis, the current investigation successfully separates two distinct constructs: one highlights the importance of flexibility and responsiveness, while the other emphasizes the significance of pace and cultural appropriateness. The results of this research have important policy and practice implications for Saudi Arabia, where educational reforms are now underway. The goal of these changes is to boost academic performance by introducing student-specific, interactive gaming into the classroom.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: AI is tanking different functions of businesses, and marketing is no exception. Digital marketing is gaining pace with the advancement in technology and the internet. The research aims to find the answer to the research question that marketers can benefit from AI in content creation for the digital market. The study also finds the relevance and use of AI in content creation and develops an AI infrastructure adoption model for content creators in digital marketing. The findings of this study were compiled using a systematic literature review that adhered to the Preferred Reporting Items for Systematic Reviews (PRISMA) statement and the criteria established by Meta-Analyses. The findings revealed that using AI in content creation provides personalized data, which helps the creators make relevant, targeted, and specific content. The research also finds that AI alone is not mature enough to carry out the whole content creation procedure as there is some limitation attached, especially regarding ethical implications. That’s why human surveillance of AI systems involved in content creation for the digital market is needed.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Adolescents increasingly turn to online sources for health information, raising concerns about the credibility of information and its impact on their behaviors. This study explores the factors shaping adolescents' online health information seeking (OHIS) behaviors. The study surveyed 381 adolescents to assess trust in online health information, eHealth literacy, parental behaviors, and AI-generated credibility scores. Structural Equation Modeling (SEM) was used to analyze data and test hypotheses based on the Social Cognitive Theory. Trust in online health information positively influenced disease-related OHIS behaviors (β = 0.24, p < 0.05) and fitness-related OHIS behaviors (β = 0.18, p < 0.05). Higher eHealth literacy correlated with increased disease-related OHIS behaviors (β = 0.32, p < 0.05) and fitness-related OHIS behaviors (β = 0.28, p < 0.05). Parental OHIS behaviors influenced adolescents' disease-related OHIS behaviors (β = 0.16, p < 0.05) and fitness-related OHIS behaviors (β = 0.22, p < 0.05). Parental OHIS mediation positively mediated these relationships (H7, H8). Higher AI-generated credibility scores associated with more disease-related OHIS behaviors (β = 0.20, p < 0.05) and fitness-related OHIS behaviors (β = 0.15, p < 0.05). Adolescents' eHealth literacy mediated these relationships (H11, H12). Trust, eHealth literacy, parental influence, and AI-generated credibility play vital roles in shaping adolescents' OHIS behaviors. Educators should prioritize enhancing eHealth literacy and promoting credible online sources to improve adolescents' health information seeking practices. This study contributes insights into the factors influencing adolescents' OHIS behaviors, emphasizing the role of parental mediation and AI-generated credibility scores. The findings inform the development of targeted health education interventions to encourage responsible online health information seeking among adolescents.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The growing significance of Artificial Intelligence (AI) across different fields highlights the essential role of user acceptance, as the success of this technology largely depends on its adoption and practical use by individuals. This research aims to examine how perceived cybersecurity, novelty value, and perceived trust affect students' willingness to accept AI in educational settings. The study's theoretical basis is the AI Device Use Acceptance (AIDUA) model. Using structural equation modeling, the study tested hypothesized relationships using data from 526 students at Jordanian universities. The results showed that social influence is positively associated with performance expectancy, while perceived cybersecurity is positively related to both performance and effort expectancy. Novelty value is positively associated with performance expectancy but a negative one with effort expectancy. Additionally, effort and performance expectancy significantly influence perceived trust and the willingness to accept AI. Moreover, perceived trust has a notable positive effect on the willingness to accept AI in education. These findings provide valuable guidance for the creation and improvement of AI-driven educational systems in universities, contributing to the broader understanding of AI technology acceptance in the educational field.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study seeks to investigate the variables that affect small and medium enterprises (SMEs) adoption of the usage of artificial intelligence (AI) and audit quality analysis from the perspectives of external auditors and accountants in the Kingdom of Saudi Arabia (KSA). Additionally, it seeks to determine whether external auditors and accountants in Saudi SMEs have different perspectives on AI adoption and how it affects audit quality. Data were gathered via an internet questionnaire from eighty accountants and forty audit companies in Saudi SMEs to accomplish these research goals. The study's findings indicate that accountants and external auditors in the KSA believe that utilizing AI improves the quality of audits. Also, it was discovered that there is no statistically significant difference in how accountants and auditors evaluate ’AI’s contribution to audit quality.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Enhancing rates of school participation holds significant importance for a nation’s educational achievements. This research employs a comprehensive approach that combines various methodologies, including multivariate regression analysis, geographic categorization, and multidimentional visualization, to examine the factors influencing school enrollment in Indonesia. Through the integration of diverse data sources, we investigate the connections among variables such as economic status, school accessibility, educational quality, and societal considerations concerning enrollment rates. This discrete impact of each factor on enrollment variations is analyzed through multivariate regression. Geospatial clustering analysis reveals enrollment trends in different regions, while multidimensional visualization untangles the intricate interplay of influencing factors. This holistic approach facilitates a nuanced comprehension of these dynamics within Indonesia’s varied geographical and society offering guidance in the formulation of more efficient strategies to improve school attendance, tackle enrollment disparities, and advocate for inclusive education based on fundamental determinants.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The objective of this study was to evaluate the impact of social media, big data, and smart technology on intercultural communication and effective leadership inside the Ministry of digital & entrepreneurship. The main objective was to investigate the influence of these technical elements on organizational behavior and the efficacy of leadership within the particular setting of a government ministry dedicated to digital economy and entrepreneurship. In order to accomplish this goal, a thorough empirical inquiry was done, which included gathering data from important individuals involved in the Ministry. The study intentionally selected a sample size of 379 individuals, who represented various responsibilities within the Ministry. The process of data gathering entailed the distribution of surveys and the conduction of interviews to acquire valuable insights and viewpoints from the participants. The utilization of this approach yielded a resilient dataset that is well-suited for thorough investigation. The study explored the complex connection between the use of social media platforms, the implementation of big data analytics, and the incorporation of smart technologies in influencing the dynamics of intercultural communication and leadership inside the Ministry. The results emphasized the substantial influence of social media in promoting intercultural communication and cooperation among personnel within the Ministry. Moreover, the implementation of big data analytics has become a crucial element in improving decision-making processes, impacting several facets of leadership efficacy, strategic planning, and employee involvement. Smart technologies were recognized as crucial elements in establishing efficient communication channels and facilitating effective leadership practices. The study's findings emphasized the beneficial impacts of utilizing social media, big data, and smart technology in the Ministry of digital & entrepreneurship. The research highlighted the significance of government organizations incorporating these technologies in a proactive manner to foster a work environment characterized by improved multicultural communication, well-informed decision-making and efficient leadership. This study makes a substantial contribution to the comprehension of how technological improvements might influence organizational behavior and leadership practices in a government setting. It provides essential insights for policymakers, leaders, and researchers. The findings have broader significance beyond the Ministry, serving as a basis for additional investigation into the use of technology in intercultural communication and leadership effectiveness inside government institutions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The Gaussian Markov Random Field (GMRF) is widely acknowledged for its remarkable flexibility, especially in the realm of high-resolution prediction, when compared to conventional Kriging methods. Rooted in the fundamental principles of Bayesian estimation, this methodology underscores the importance of a meticulous examination of prior and hyperprior distributions, along with their corresponding parameter values. Sensitivity analyses are crucial for evaluating the potential impact of these distributions and parameter values on prediction results. To determine the most effective values for hyperprior parameters, an iterative trial-and-error approach is commonly employed. In our research, we systematically assessed a variety of parameter values through exhaustive cross-validation. Our study is focused on optimizing hyperprior parameter values, with a particular emphasis on Penalized Complexity (PC). We applied our method to conduct spatiotemporal high-resolution predictions of PM2.5 concentrations in Jakarta province, Indonesia. Achieving accurate predictive modeling of PM2.5 concentrations in Jakarta is contingent upon this optimization. We identified that the optimal values for PC hyperprior parameters, with a range of less than 2,000 and a hyperprior standard deviation greater than 1 with a 0.1 probability, yield the most accurate predictions. These parameter values result in the minimum mean absolute percentage error (MAPE) of 19.35393, along with a deviation information criterion (DIC) of -154.23. Our findings highlight that the standard deviation parameter significantly influences model fit compared to the relatively insignificant impact of the range parameter. When coupled with high-resolution mapping, these optimized parameters facilitate a comprehensive understanding of distribution patterns. This process aids in detecting areas particularly susceptible to risks, thereby enhancing decision-making efficacy regarding air quality management.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This paper aims to investigate if trust, perceived usefulness, and perceived ease of use affect the intention to use e-payment. Also, the study explores if attitudes towards the use of e-payment influence consumer's intentions to use the e-payment system which is supported by testing the moderation effect of Self-Efficacy, and Computer Anxiety on the attitude to use such systems in higher education institutes. The study found that there are a variety of effects of the Electronic Payment Acceptance Model in the United Arab Emirates that pertain to sociological, legal, and economic aspects. The United Arab Emirates can benefit from a more robust and inclusive digital payment ecosystem by comprehending and implementing the lessons gained from such research. Among the lessons learned from this study is that using electronic payment leads to many benefits, it is not possible to benefit from all these benefits if the acceptance rate of technology, especially electronic payment, is low. For this reason, this research came to provide solutions to the possibility of increasing the acceptance of technology among individuals and organizations through a complete model and studying the impact of its factors and the factors that moderate the relationship in it.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: To ensure that national development objectives in rural areas are achieved evenly and sustainably, the Government of Indonesia applies the principles of Village Sustainable Development Goals (SDGs), which are derivative programs of SDGs. One of the indicators in measuring the progress and independence of villages in Indonesia is the availability of cellular phone signal access. Cellular phone signals have a vital role because most internet users in Indonesia rely on mobile data connections from cellular operators. However, the signal emitted by a provider tower has a limited range. According to the data of the Developing Villages Index in 2022, Tasikmalaya Regency is one of the regencies with the highest number of villages that have weak signal strength in West Java Province, Indonesia. To examine the effect of distance and height difference between the placement of the nearest provider tower and the location of the Village Office on the internet signal strength category in Tasikmalaya Regency, Logistic Spatial Autoregressive modeling is needed. In this study, the Bayesian Markov-Chain Monte Carlo estimation method was used, because it has advantages in flexibility and computational efficiency. In spatial modeling, there is a spatial weight matrix determined by the researcher’s understanding of the observed phenomenon. The variable observed in this study is signal strength, which has an orientation at a distance. However, there are several types of distance-based spatial weight matrices, such as K-nearest neighbor, radial distance, power distance, and exponential distance. To determine the most suitable distance-based spatial weight matrix in internet signal strength modeling, the four (4) weight matrices were compared based on the goodness of fit measure models, calculated from the confusion matrix. The results of the analysis showed that the radial distance weight matrix with a threshold distance of d = 1.7km is the most suitable use of distance-based spatial weight matrix in internet signal modeling in Tasikmalaya Regency. The weight matrix exerted a positive spatial autocorrelation effect of 57.141%. In addition, the height difference factor between the location of the provider tower with the location of the village office has a greater effect than the horizontal distance.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: As time passes, social media, which was formerly used as a means of communication between users, is experiencing a transition as a means for broadcasting information, conducting business, advertising, and even political campaigning. In elections, social media is also used to discredit political opponents to reduce the electability of opposing candidate. Spreading hate speech and fake news to undermine the electability of opposing candidate is a common violation of the law committed by supporters of one candidate over another. Considering that the number of social media users increases annually at a very rapid rate, the hazard of social media abuse has the potential to grow. In 2022, Indonesia had 191 million social media users in January 2022. Obviously, this will make the election situation more tumultuous and has the potential to cause societal divisions. The government must have a control system in place to screen social media content that can be considered illegal. In this study, fake news and hate speech are classified using the Bidirectional Gated Recurrent Unit (BiGRU). Lastly, K-Prototype was used to do clustering based on categorization dimensions and probable distribution to identify which clusters had the greatest risk of breaking the law, creating confusion, and dispersing broadly throughout society. It is hoped that the clusters that are created will represent the levels of priority of tweet data that requires prompt attention from the government to prevent it from spreading and inciting social unrest. Based on the results of the analysis, the BiGRU fake news model yields a F1-score of 95%, while the BiGRU hate speech model yields a F1-score of 90%. Clustering data using K-Prototype in this research can reduce the number of tweet data from 13,183 to 1,791 data. These new data are considered as a priority that must be pursued in preventing social media disputes.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Growing environmental concerns have led to increased demand for ‘green’ or environmentally friendly business. This has resulted in growing interest in the research of Green Information Technology (GIT). However, to date, such research has had a disproportionate emphasis on organisational antecedents while often overlooking outcomes. The current study aims at giving a better insight into the state of GIT adoption among oil companies in Sudan. If these companies were to adopt a green business model, it would significantly impact the environment given that they typically contribute significantly to environmental degradation. To this end, this study a) determines the level of awareness of GIT adoption among employees of oil companies in Sudan, b) identifies the key factors affecting the GIT adoption, c) examines the effect of training, top management support, perceived ease of use, perceived usefulness, relative advantages, and GIT behaviour on GIT adoption, and (d) examines the effect of GIT adoption on outcomes, namely business performance, competitive advantage, and process innovation. From a sample of 292 respondents, the result revealed that top management and GIT behaviour were two of the four antecedents not supported by data, thereby rendering them insignificant. Surprisingly, the survey data supports all three hypotheses that recognise a positive relationship between GIT adoption and the outcomes. This study provides important empirical evidence from oil companies that lack a green adoption policy that encourages them to consider joining the green bandwagon. The study concludes that most respondents are aware of GIT.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The primary objective of this study was to assess the challenges associated with the digital transformation process in the accounting systems of companies listed on the Khartoum Stock Exchange, focusing on the perspectives of senior management, financial management, and technology management. These departments were considered integral due to their profound understanding of digital transformation processes, requirements, and existing as well as anticipated challenges. Employing a descriptive-analytical approach, the study utilized a questionnaire to gather data from 315 individuals within the study population. The results revealed a favorable inclination among Khartoum Stock Exchange-listed companies towards digital transformation, manifested through a notable automation of accounting procedures, the cultivation of a digital culture, and the adoption of strategic approaches for digital transformation. However, the study identified several challenges, including insufficient technological infrastructure at the national level, the absence of a clear national strategic plan for digital transformation, and limited financial resources allocated to digital transformation in accounting systems. The study also proposed a set of solutions to address these challenges, categorized into national and corporate levels.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study presents a structural equation model to describe the interrelationships between Digital Marketing, Brand Articulating Capability, Brand Resonance Capability, and Marketing Performance. It employs a cross-sectional study to examine the relationships among those research variables. This study utilized a survey methodology, which involved gathering data from 292 participants who were representatives of small and medium enterprises (SMEs) in South Sulawesi, Indonesia. Out of the 292 questionnaires distributed, 270 were considered appropriate for analysis. Four hypotheses were formulated and examined by employing structural equation modeling (SEM) analysis, which revealed several noteworthy findings. The results suggest that SMEs with a stronger focus on digital marketing are more likely to enhance their capacity to articulate their brand, leading to improved marketing effectiveness. In contrast, those with a higher level of Digital Marketing tend to acquire brand resonance capabilities. The findings of this study highlight the significance of the Brand Articulating Capability and Brand Resonance factors in improving the impact of Digital Marketing on Marketing Performance, hence facilitating the growth of SMEs.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study on the moderating effect of electronic quality in mobile marketing aims to examine the factors that influence how Saudi commercial banks are viewed by their customers. A research framework that sheds light on the state of the research was developed after a comprehensive analysis of the accessible literature. The theoretical foundation of this study is the idea of perceived characteristics, which identifies five critical factors that influence adoption rates. The empirical results of this study are presented based on a sample of 300 respondents (n = 300). The research was conducted using the statistical technique of least squares structural equation modeling (PLS-SEM). The reporting format conforms to accepted PLS-SEM analysis standards. The results reveal a significant association between mobile marketing and customer perceptions in the context of Saudi commercial banks, especially when electronic quality is used as a mediating variable. Based on these findings, we suggest that Saudi commercial banks should strategically include e-quality in their digital marketing campaigns, paying special attention to mobile marketing.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Heading towards a cashless society, consumers have undergone a significant shift toward mobile payment services after COVID-19. The proliferation of various mobile payment applications has resulted in low consumer loyalty to mobile payment providers. Thus, continuance intention of mobile payments becomes crucial for mobile payment providers. The integration of UTAUT2 and the dedication-constraint-based mechanism are adopted to elaborate approach in retaining customers. The dedication mechanism is built by examining antecedents of satisfaction. Meanwhile, the constraint mechanism is driven by switching costs, preceded by habit and economic incentives. A total of 297 mobile payment users participated by filling out questionnaires in a field survey. The results show that the dedication mechanism dominates in creating satisfaction by increasing perceived usefulness, while the constraint mechanism is more influenced by habit than economic incentives. This research provides insights for mobile payment providers to enhance satisfaction by understanding consumers' needs in using mobile payments and to increase switching costs by fostering habit, thereby encouraging continuance intention of mobile payments in the future.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The rapid advancement of technology has had a significant impact on a wide range of industries, including the auditing industry. It is now obvious that employing Computer Assisted Auditing Techniques (CAATs) is a possible tactic for enhancing the effectiveness and efficiency of the audit process. This study evaluates how CAATs affect auditors' expectations for performance and effort in Jordan. Through a comprehensive survey of Jordanian auditors, this research provides insights into the factors that drive CAATs adoption. Utilizing structural equation modeling, the study confirms that both Effort Expectancy and Performance Expectancy positively influence CAATs adoption. These relationships are supported by robust path coefficients and low P-values, indicating statistical significance. The results of this study should clarify the possible advantages of including CAATs in the audit process and point out any difficulties auditors could encounter. Companies and professionals may choose wisely whether to embrace and use CAATs by comprehending Performance Expectancy and Effort Expectancy.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Recently, there has been tremendous interest worldwide in the possibility of using chaos in communication systems. Many different chaos-based secure communication schemes have been proposed up until now. However, systems with strong chaoticity are more suitable for chaos-based secure communication. From the viewpoint of Lyapunov exponents, a chaotic system with a larger positive Lyapunov exponent is said to be more complex. This paper constructing a multistable chaotic system that can produce coexisting attractors is an attractive field of research due to its theoretical and practical usefulness. An innovative 3D dynamical system is presented in this research. It can display various coexisting attractors for the same values of parameters. The new system is more suitable for chaos-based applications than recently reported systems since it exhibits strong multistable chaotic behavior, as proved by its large positive Lyapunov exponent. Furthermore, the accuracy of the numerical calculation and the system's physical implementations are confirmed by analog circuit simulation. Finally, implementing the proposed voice encryption is done using a four-wing chaotic system based on the PRNG.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Social media has become a forum for discussion formed with the rapid development of internet technology. Using the internet makes getting various information according to your needs more leisurely. This research aims to determine the influence of social media marketing on customer loyalty in the use of streaming application technology as a form of technology acceptance model. Data collection was carried out in 2020 -2023 with 1294 respondents spread across several provinces in Indonesia. The data obtained were analyzed using SEM-PLS. The data processing results to answer the research hypothesis showed that social media marketing as a product promotion tool positively impacted increasing perceived usefulness, enjoyment, and brand trust. The perceived usefulness obtained influences increasing brand trust but does not impact increasing perceived enjoyment. Streaming application technology with the growing feeling of being entertained and accessing online movies to get happiness as a form of perceived enjoyment affects brand trust by getting the benefit that the product used meets expectations and never disappoints. Perceived enjoyment and brand trust increase customer loyalty by increasing the number of active users who recommend online films to other people and staying positive about streaming technology on social media. The practical contribution of the research is optimizing social media as a company marketing tool for the film business to promote newly released films in the community of social media users. Theoretical contribution by enriching consumer behavior theory and technology acceptance models in the application of streaming technology in online film access.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The financial performance of a company reflects its ability to run and manage its operations while strictly adhering to prudent financial administration principles. Good financial performance often mirrors the implementation of Good Corporate Governance (GCG) principles in a company. The application of GCG provides a solid foundation for a company to conduct its operations transparently, ethically, and accountability. The objective of this research is to analyze the implementation of GCG and the capabilities of big data analysis on financial performance, as well as to examine the mediating role of big data analysis in the relationship between GCG and financial performance. The research method employed is quantitative, and data were obtained through a survey questionnaire distributed using a Likert Scale of 1-5. Random sampling was employed to select 258 samples from manufacturing companies that are State-Owned Enterprises (SOE/BUMN) listed on the Indonesia Stock Exchange (ISE/BEI). Data collection took place from March 2023 to May 2023. Respondents included staff and managers from these BUMN companies. The collected data were analyzed using Structural Equation Modeling (SEM) with SmartPLS software. The research findings indicate that GCG has a positive and significant influence on big data analysis, providing a foundation for digital transformation. Furthermore, GCG also contributes positively and significantly to the financial performance of the company. Big data analysis has proven to have a positive impact on financial performance, indicating the role of technology in optimizing financial results. Another interesting finding is that big data analysis mediates the relationship between GCG and financial performance, highlighting the crucial role of technology in connecting good corporate governance practices with optimal financial outcomes.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study tried to explain the effect of digital marketing, supply chain integration, and innovation capabilities in increasing competitiveness and creative industries performance. There were three creative industry business sectors as units of analysis, namely culinary, craft and fashion sectors. A quantitative approach was used through a survey of 163 creative industries located in five regions i.e.: Makassar City, ParePare City, Wajo Regency, Tana Toraja Regency and North Toraja Regency. While respondents were business owners, managers, and supervisors. Descriptive statistics, and structural equation modelling as a method of analysis. Results showed that digital marketing and integrated supply chain significantly influences competitiveness as well as creative industry performance. Meanwhile, innovation capability significantly influences competitiveness, but not significantly on creative industry performance. This study also proved that competitiveness significantly affected creative industry performance. In addition, this study also confirmed that competitiveness mediated partially on effect digital marketing and integrated supply chain toward business performance and mediated fully on effect innovation capability toward business performance, primarily in the context of creative industry development.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study intends to evaluate the role that spiritual destination image plays in mediating the effects of attachment to virtual tours and the promotion of spiritual destinations through social media with the intention to revisit spiritual places in Bali. The research primarily examines individuals who have participated in tourism-related endeavors and visited spiritual destinations in Bali. A purposive selection strategy was used to choose a sample size of 160 tourists for the study. The analytical methodology employed in this study involves the utilization of Path Analysis, specifically implementing Structural Equation Modeling with Partial Least Squares (SEM-PLS). The study found that emotional attachment with virtual tours improves the spiritual destination's image and intention to revisit. The impact of social media promotion on the perception and intention to revisit a spiritual place has been found to be substantial and beneficial. Furthermore, the portrayal of the spiritual destination has a notable and favorable impact on an individual's propensity to partake in subsequent visits. Furthermore, the image of a spiritual destination is able to mediate attachment to a virtual tour and social media promotion with the intention to revisit partially. Hence, it is imperative for managers overseeing spiritual destinations in Bali to consistently devise virtual tour models and employ social media promotions to enhance the image of these spiritual destinations. This strategic approach aims to augment tourists' inclination to visit such destinations, thereby fostering sustainable tourism practices in Bali.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The COVID-19 pandemic has brought about significant transformations in various aspects of life. Shifts in consumer behavior, for instance, can exert influence on global economic operations. This situation indirectly boosts the e-commerce sector while expediting the decline of conventional retail. Matahari Department Store is an example of a retail business adapting to this trend. Matahari, a retail company, recently shifted its focus towards online marketing. On one of its social media platforms, Matahari consistently presents engaging content. Nevertheless, this does not necessarily imply that Matahari enjoys a high level of social media engagement. This study aims to evaluate how brand equity influences engagement behavior, with engagement goals acting as a mediator, while considering social media context as a moderating factor. The research employed a quantitative approach with a causal orientation. The target population for this study comprises the followers of the Matahi Department Store Instagram account. The sampling method employed was purposive, indicating that the sample was selected based on specific criteria. Data collection was conducted through the online distribution of questionnaires using Google Forms. The collected data was analyzed through the utilization of SMART PLS 3.0 software employing the Structural Equation Modeling (SEM) method. As per the research results, brand equity is influenced through engagement intention and exhibits a positive and statistically significant impact on both consumption and donation behavior. Additionally, the connection between intention to be involved and behavior in consumption is affected by media richness.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The potential for transforming the estate management industry through the resolution of common inefficiencies, lack of transparency, and security concerns is presented by the use of blockchain technology into estate governance. The purpose of this article is to clarify how incorporating blockchain technology would affect estate operations and governance. This study is based on quantitative information that was collected from 317 estate management professionals using a 5-point Likert scale questionnaire. SmartPLS4 analysis demonstrates that blockchain governance has a statistically significant and robust influence on estate governance in Jordan. The impact of Blockchain Governance on Jordanian Estate Management appears to be negligible and unimportant. Furthermore, there appears to be a negligible and insignificant correlation between Jordanian estate management and estate planning methods. In-depth analysis of these theories is done in this article, which also offers insights into how blockchain technology affects estate governance dynamics and how it can affect Jordan's estate management procedures. The consequences go beyond theoretical understandings; they promote the use of blockchain technology in estate governance frameworks as a game-changing means of ensuring the safe, transparent, and effective administration of frozen estates in Jordan and elsewhere.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The objective of the study is to clarify the influence of digital capabilities on innovation capability, considering the direct and indirect impacts of digital leadership and digital culture in small and medium enterprises (SMEs) in Vietnam. The study used a mixed research method including qualitative with in-depth interviews and quantitative with Partial Least Squares Structural Equation Model (PLS-SEM) to analyze 271 responses. Research results show that digital capabilities have a positive impact on SMEs’ innovation capability. Digital leadership and digital culture also, directly and indirectly, affect firms’ digital capabilities and innovation capabilities. From there, the study confirms the theoretical contributions as well as proposes suggestions for SMEs to develop digital capabilities, and as a result, to develop innovation capabilities.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The objective of this research is to comprehend how these elements interact to influence young people's subjective happiness and to provide insightful information about their perspectives. Significant discoveries are shown by the study's findings. This research paper conducts a thorough analysis of the many factors that affect youth happiness, including GDP, loneliness, longevity, autonomy, generosity, and corruption. First off, GDP shows up as a significant and noticeably positive factor to young happiness. This emphasizes how crucial economic success is in raising young people's life happiness. Second, autonomy is recognized as another important factor, showing a significant and favorable influence on happiness. It emphasizes how important one's own independence and life control are for young wellbeing. Additionally, the study uncovers a diverse range of impacts among these indicators. Longevity and Generosity are found to positively influence happiness, emphasizing the role of health and social support in young people's contentment. Conversely, Loneliness and Corruption exhibit significant negative effects on happiness, underscoring the detrimental consequences of social isolation and institutional corruption on youth well-being. In conclusion, this research paper offers a holistic view of youth happiness, recognizing the multifaceted nature of its determinants. These findings have important implications for policymakers, highlighting the need to address not only economic aspects but also personal autonomy, social connectedness, and integrity in efforts to promote youth happiness and well-being in society.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research uses Technology Acceptance Model to explore the elements influencing students' attitudes toward using Chat Generative Pre-Trained Transformer (ChatGPT), a recently developed artificial intelligence (AI) tool, for learning and educational purposes. Using Amos version 23 structural equation modelling and 880 student survey responses, the suggested model was empirically tested. According to the report, students think well of ChatGPT utilization in the classroom. Credibility, Usefulness and ease of use, all influence how positively people feel about using this technology in a classroom setting. The study's findings, however, did not support the notion that students' adoption and use of ChatGPT was insignificantly influenced by perceived enjoyment. Moreover, the results conclude that attitude mediates the relationship between usefulness and intention to use ChatGPT. The research will help businesses, educational institutions, and the global community by providing insight into how students view the ChatGPT service within a learning environment. Additionally, the application boosts learners' confidence and interest, which improves general awareness and literacy. Finally, the research will facilitate developers of AI in the betterment of their product and service delivery and regulators in regulating the use of AI-based bots. Owing to its recentness, there is not much study currently available on ChatGPT use in education. This research adds significantly to the extant knowledge on the adoption of advanced education technologies by examining the adoption characteristics of ChatGPT, a novel AI-based tool involving students. Additionally, there is a dearth of research in the literature on students' adoption of ChatGPT for educational purposes. Such a gap was filled as this study identified the factors affecting students' adoption of ChatGPT in the classroom.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Accounting systems have experienced significant developments, including sophisticated software applications, automation, big data, data analytics, and so on. The purpose of this study is to examine the effect of digitalization of accounting systems on the quality of accounting information and the effectiveness of management decision making in small and medium enterprises (SMEs) in a developing country, Indonesia. Based on the innovation diffusion theory, the hypothesis states that digitalization of the accounting system can improve accuracy and timeliness, cost reduction, and decision making. Data were obtained from questionnaire surveys to SMEs who had implemented the digitalization of the accounting systems. The results showed that the digitalization of the accounting systems had a positive effect on the accuracy and timeliness of accounting information and cost reduction. Furthermore, these two variables had a positive effect on the effectiveness of SME management decision making.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Operational data is always huge. A preprocessing step is needed to prepare such data for the analytical process so the process will be fast. One way is by choosing the most effective features and removing the others. Feature selection algorithms (FSAs) can do that with a variety of accuracy depending on both the nature of the data and the algorithm itself. This inspires researchers to keep on developing new FSAs to give higher accuracies than the existing ones. Moreover, FSAs are essential for reducing the cost and effort of developing information system applications. Merging multiple methodologies may improve the dimensionality reduction rate retaining sensible accuracy. This research proposed a hybrid feature selection algorithm based on ScC and forward selection methods (ScCFS). ScC is based on stability and correlation while forward selection is based on Random Forest (RF) and Information Gain (IG). A lowered subset generated by ScC is fed to the forward selection method which uses the IG as a decision criterion for selecting the attribute to split the node of the RF to generate the optimal reduct. ScCFS was compared to other known FSAs in terms of accuracy, AUC, and F-score using several classification algorithms and several datasets. Results showed that the ScCFS excels other FSAs employed for all classifiers in terms of accuracy except FLM where it comes in second place. This proves that ScCFS is the pioneer in generating the reduced dataset with remaining high accuracies for the classifiers used.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Establishing new relations with new customers and managing customers’ relations with the existing ones is important and considered challenges for each firm nowadays. Thus, studying and understanding different psychological factors like consumers’ emotions and happiness, motivates and attitudes are important while it helps in how to do more business with customers and push them to stay longer especially when adopting e-government mobile applications. This study used a quantitative research approach with survey data collection from different users of government mobile applications (GMA). The sample is around 340 from different backgrounds and levels of using different government services mobile apps. The results revealed the standardized regression and coefficients interpret the direct association between the study variables, hence confirmed the hypothesized model that included several factors such as perceived usefulness, perceived ease of use, perceived skills readiness, and perceived security toward attitudes to GMA and use of GMA effects on customer happiness and positive emotion. Moreover, the conclusion and implications confirmed the literature of this research field and elucidated most of the stated factors that significantly influence the customers’ emotion and happiness. For further study, research directions are given to expand the extant understanding of new different factors with other outcomes of mobile applications use.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The current study aimed to examine marketing cyber-security (DDoS Attacks, Cross-Site Scripting, SQL Attacks, and passwords attacks) in the digital age by presenting evidence from digital marketing platforms. Depending on the quantitative approach and utilizing a questionnaire as a tool, (133) marketing managers in digital marketing companies in Jordan responded to an online questionnaire. SPSS was used to screen and analyze the gathered data. Results of the study accepted the main hypothesis, and it appeared that marketing cyber-security has a statistically positive influence on marketing platforms, in addition to that, it appeared that the highest influence of sub-variables was for the benefit of Structured Query Language (SQL) Attacks explaining 35.8% of the variation. This result meant that SQL attacks-security does have a statistically positive influence on marketing platforms. This hypothesis could be tested through various methodologies, for example, surveys, interviews, focus groups, and/or experiments. The study recommended that marketers should use role-based access to limit the data employees can access and regularly review their permissions. Further recommendations were presented in the study.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Active Queue Management (AQM) techniques are crucial for managing packet transmission efficiently, maintaining network performance, and preventing congestion in routers. However, achieving these objectives demands precise traffic modeling and simulations in extreme and unstable conditions. The internet traffic has distinct characteristics, such as aggregation, burstiness, and correlation. This paper presents an innovative approach for modeling internet traffic, addressing the limitations of conventional modeling and conventional AQM methods' development, which are primarily designed to stabilize the network traffic. The proposed model leverages the power of multiple Markov Modulated Bernoulli Processes (MMBPs) to tackle the challenges of traffic modeling and AQM development. Multiple states with varying probabilities are used to model packet arrivals, thus capturing the burstiness inherent in internet traffic. Yet, the overall probability is maintained identical, irrespective of the number of states (one, two, or four), by solving linear equations with multiple variables. Random Early Detection (RED) was used as a case study method with different packet arrival probabilities based on MMBPs with one, two, and four states. The results showed that the proposed model influences the outcomes of AQM methods. Furthermore, it was found that RED might not effectively address network burstiness due to its relatively slow reaction time. As a result, it can be concluded that RED performs optimally only with a single-state model.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research attempts to better understand how students in Saudi Arabia benefit from narrative and story aspects in gamified learning environments. Data from a sample of 500 persons with varying levels of education are analyzed using quantitative methods such as descriptive statistics, correlation analysis, and multiple regression analysis. The findings point to strong positive correlations between the use of gamification in education, the influence of storytelling, narrative variables, and the acquisition of new skills. There has been a significant shift toward the use of narrative variables as measures of mastery in gamified classrooms. This study's results show that using gamified learning with story elements may increase students' interest, motivation, and knowledge retention. Efforts are now being made by Saudi Arabia to update its educational system and provide its youth with the tools they'll need to succeed in the country's emerging knowledge-based economy. The use of game-based learning and narrative-rich experiences has promising results in this setting.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study empirically examines the impact of strategic thinking on organizational excellence in Jordan's Information and Communication Technology (ICT) sector. Adopting a quantitative methodology, this study surveys a sample of 270 individuals drawn from various ICT companies across Jordan. Utilizing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) for analysis, the study investigates the effects of different dimensions of strategic thinking on organizational excellence. The findings reveal that among the dimensions studied, dynamic and systematic thinking significantly and positively influenced organizational excellence. These results underscore the critical role that adaptive and methodical approaches to strategic thought play in enhancing organizational performance and competitiveness within the fast-paced ICT sector. The study not only contributes to the theoretical understanding of strategic thinking's relevance in organizational success but also offers practical insights for ICT companies aiming to achieve excellence in a dynamic business environment.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The rapid growth of electronic transactions has transformed the landscape of many industries, especially in the banking sector. This digitalization growth has brought about the need to understand the impact of the adoption of electronic banking in rural banks on the financial performance of rural banks in Indonesia. The aim of this research is to analyze the extent to which the adoption of e-banking influences consumer electronic trust (e-trust) and financial performance. The research method used is quantitative, involving data collection through questionnaires. Respondents in this study are managers of rural banks in West Java, Indonesia. The sample size used is 200 participants. Data collection took place over two months from May to June 2023. Data analysis was performed using Structural Equation Modeling (SEM) through SmartPLS 4 software. The research results indicate that the adoption of e-banking has a positive and significant impact on consumer e-trust and financial performance. Consumer e-trust has also been proven to mediate the relationship between e-banking adoption and financial performance. These findings provide profound insights into how e-banking plays a key role in building consumer e-trust and enhancing the financial performance of banking institutions. This research makes a significant contribution in the context of developing e-banking strategies in the banking sector. The implications of these findings can guide policies, strategies, and innovations in the banking sector to optimize the benefits of electronic banking, build consumer e-trust, and enhance financial performance in this digital era.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Time series data clusters are being researched thoroughly. The distance metric drives the development of the clustering time series. The ARIMA model is one of the models that can be employed in model-based clustering, although differing model selection criteria can lead to uncertainty in the model. In this investigation, we created a technique for ensemble distance-based time series data clustering. To express the distance between two series, five distances based on the five model selection criteria are utilized. The average of the five distances reflects the distance of two time series data. According to the simulation results, the ensemble distance method could boost clustering accuracy by more than 11%. Based on the pattern of rainfall levels, we applied our methods to find clusters of locations in the Province of West Java (Indonesia). The findings indicate that the rainfall pattern in the same cluster is similar. The cluster model is effective and feasible for representing individual models in a cluster.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The current research paper aims to pinpoint the determinants that impact consumers' perceived ease and perceived usefulness of digital wallet usage in Jordan. To accomplish this, the Technology Acceptance Model (TAM) has been used, which encompasses additional dimensions like the perceived risk of COVID-19, social influence, government support, promotional benefits, perceived value, and personal innovativeness. A quantitative research approach was employed in this paper; an online survey was applied to gather data from a total of 401 participants. The gathered data underwent analysis using a two-step PLS-SEM method. The study outcomes show that digital wallet users' perception of promotional benefits and perceived value significantly and positively affect the digital wallet's perceived usefulness. However, governmental support and social influence do not have a significant impact on digital wallets' perceived usefulness.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The English language for English Instructed Class students as the end-users of Higher Education is an integral part of the sustainability of globalization in Indonesia. The research investigates the relationship between brand image, price, web quality, and student satisfaction in conducting English-instructed classes. The data was obtained via an online inquiry form 105 respondents and analyzed using Partial Least Square (PLS). The findings show that the influence of the brand image on student satisfaction, price towards student satisfaction, and web quality on student satisfaction are significant. The results illustrate that English-instructed class students' happiness depends on how the institution creates the brand image, offers competitive tuition, and develops web quality to attract prospective English-instructed class students.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Higher education is currently facing a myriad of complex and diverse challenges. Increasing global competition, rapid developments in educational technology, and mounting pressures related to cost management and financing are factors that can significantly impact the higher education landscape. The aim of this research is to analyze the extent to which social media use can enhance organizational performance, ultimately influencing the organization's ability to foster innovation. This study employs a quantitative approach, collecting data through a questionnaire distributed to 205 respondents, consisting of faculty members working in private universities in Bandung, Indonesia. The questionnaire is designed using a 7-point Likert scale and distributed through an online survey platform. The research findings indicate that social media use has a positive and significant relationship with organizational performance and innovation performance in higher education. These findings are reinforced by the mediating role of organizational performance, explaining a significant portion of the positive influence of social media on innovation performance. The implications of these findings provide a foundation for universities to optimize the use of social media as a strategic tool in achieving performance goals and fostering innovation in the higher education environment.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: As a potential treatment intervention for youngsters with Social Anxiety Disorder (SAD) in UAE, this study aims to investigate the use of virtual reality socialization groups on the widely used social media platform Facebook. The purpose of this research is to examine how social anxiety, sadness, and anxiety symptoms change after receiving treatment. The quantitative approach used in the study yields very small impact sizes. No discernible differences emerged, however, between the test and control groups at the statistical level. It investigates how cultural factors, including the unique social norms and expectations in UAE, play a crucial role in determining the success of interventions. Specifically adapted virtual reality therapies for various cultural settings are emphasized. In addition, it highlights the importance of understanding the therapeutic implications of small effect sizes. Prospective research directions are explored in this article; special attention is paid to the development of ever-better technologically-driven treatments across a variety of cultural settings.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The present study examines the effect of variables on contemporary management accounting practices' adoption in the public sector. The present research further investigates the relationship between the uptake of contemporary management accounting practices and organizational performance and change. 520 surveys were mailed to the public sector in Jordan to gather data, which was subsequently analyzed employing SEM. The findings of the research indicate that there are substantial relationships between accounting staff qualifications and management accounting practices. Results indicate that modern management accounting practices could help public sector practitioners enhance performance and promote organizational change. The investigation offers concrete insight into the public sector's uptake of management accounting practices. The research conducted offers a field study of the impact of implementing a suite of management accounting practices in the public sector.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study examines the robust relationships between Roblox's business model, collaborative learning, participation in the decision-making process, and cooperative literacy within the Indonesian Roblox community. All hypotheses were substantiated, emphasizing the significance of understanding the business model, promoting collaborative learning, and encouraging active involvement in decision-making activities for fostering cooperative literacy among players. The research employed an exploratory research design with a quantitative approach. Sampling bias and self-reported data are acknowledged limitations, along with the cross-sectional design's inability to establish causality. To address these constraints, future research should employ longitudinal methods, diverse data collection approaches, and intervention studies. Cross-cultural research comparing the Indonesian Roblox community with other cultural contexts is also encouraged. Practical recommendations include integrating features that support collaborative learning and decision-making participation within the Roblox platform. Collaboration between educational institutions and Roblox to use the platform as an educational tool is suggested, offering students a unique opportunity to develop cooperative literacy skills. These findings offer valuable insights into cooperative literacy and community engagement within the Roblox ecosystem, providing a roadmap for its development. This research contributes to the platform's growth and success in Indonesia, making it a more cooperative and informed community.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In higher education institutions, effective digital communication is crucial for achieving administrative goals, such as improving student services, managing resources, and facilitating collaboration among staff members. By exploring the impact of copresence factors on digital communication effectiveness, higher education institutions can gain a deeper understanding of the factors that influence their digital communication and develop strategies that optimize its efficiency. The study applied a quantitative research approach through a questionnaire survey to collect required responses from employees who are working in the higher education institutions of Jordan with a total of 304 participants. The findings of this study indicate that copresence factors play a significant role in the effectiveness of digital communication within higher education institutions in Jordan. The results support the framework developed by others and suggest that self-copresence and partner-copresence have a positive impact on the efficiency of communication. This highlights the importance of considering the presence of individuals during digital communication and the impact it can have on the quality of the exchange. In conclusion, the study sheds light on the importance of correspondence in digital communication and its impact on the efficiency of communication within higher education institutions. The findings can help in the development of strategies and practices for enhancing the effectiveness of digital communication and improving administrative work in higher education institutions in Jordan.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In the changing educational environment brought about by the COVID-19 pandemic, this study investigates the dynamic interactions between digital citizenship, digital empowerment, and academic performance. Data is collected from a survey of students at the College of Business, Al-Ahliyya Amman University. The Partial Least Squares (PLS) method of structural equation Modeling (SEM) was used to analyze the collected data. The findings reveal how digital empowerment is directly impacted by digital education, respect and protection. It was also discovered that digital empowerment directly improves academic performance, highlighting the significance of promoting digital settings that are safe, respectful, and conducive to learning. With the changing educational landscape, this study adds to a better understanding of how digital citizenship influences students' academic performance and learning experiences. It provides educators, organizations, and legislators with useful information to help them better prepare students for success in a fast-evolving educational landscape by enhancing their digital skills and competences.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study investigates the impact of game-based (gamification) e-Learning techniques on students' engagement, thereby, their satisfaction with e-learning in Jordanian private universities. A conceptual model was developed based on existing empirical evidence from the literature. Data was then collected through a self-administered questionnaire survey from 198 private university students, who were conveniently selected for the study. The data was analyzed using Structural Equation Modeling (SEM) with smart PLS 23. Data analysis revealed a positive effect of gamification on both student engagement and satisfaction, suggesting that incorporating gaming elements into the e-learning process in Jordanian private universities led to higher levels of student engagement, thereby greater student satisfaction with the e-learning experience. A mediating role was also found for student engagement on the effect of gamification on student satisfaction. The findings provide insights to practitioners on how gamification can be utilized as an effective strategy to deliver a more enjoyable and interactive e-learning experience. Research findings were discussed, and conclusions and implications were lastly provided.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The study aims to investigate the impact of Pentagon Fraud Model in five key factors, namely Pressure, Opportunity, Rationalization, Capability, and Action, on the risk of Financial Statement Fraud (FSF). Additionally, it explores the moderating role of Islamic Corporate Governance (ICG) in the relationship between these factors and FSF. The research employed a quantitative approach, utilizing survey data from a sample of 270 respondents. The findings support the hypotheses that all five factors significantly influence FSF, with Pressure exerting the highest impact. Furthermore, ICG is found to moderate the relationships between these factors and FSF, underscoring its role in reducing financial fraud risk. Practically, this study offers essential guidance for organizations in managing FSF risks more effectively. Integrating ethical and governance principles, as moderated by ICG, can help strengthen internal controls, ethics training, and a culture of integrity. Policymakers should consider these findings for enhancing regulatory frameworks, and educational institutions can integrate these results into their curriculum. The study's contribution lies in shedding light on the significance of ICG as a risk-mitigating factor in the context of FSF. The findings provide valuable insights for academics, practitioners, and policymakers. They enhance the understanding of FSF and its mitigating measures and offer a foundation for further research in the field.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to explore the ways in which the use of WhatsApp for diagonal and lateral communication can improve the achievement of tasks, to what extent it can keep data and information trustworthy and confidential, and in what ways WhatsApp improves the communication of suggestions, instructions, and complaints. The study uses a quantitative research strategy with one independent variable, which is WhatsApp usage in the workplace, and three dependent variables, which are team member communication, employee performance, and confidentiality. To test the proposed research model, the authors conduct an online questionnaire in the United Arab Emirates. Descriptive statistics are used to analyze the quantitative data collected through the questionnaires. The study shows that the use of WhatsApp for communication is positively associated with leader-member exchange (LMX) and team-member exchange (TMX). Both LMX and TMX have a positive correlation with employee performance. WhatsApp is a trusted method to transfer information between team members and between managers and employees. The study also asserts that the use of WhatsApp is an effective tool to improve productivity and performance, and it makes task completion faster. It appears that the study has a limited literature review and lacks previous research on the variables related to data confidentiality and improving team performance. In this case, the study seems to be lacking a thorough examination of prior research related to data confidentiality and its impact on team performance. WhatsApp is a widely used messaging application that offers end-to-end encryption to its users, and this encryption provides a certain level of security and privacy. WhatsApp usage has a positive impact on team performance and productivity. The study presents a concrete understanding of how vertical and horizontal relationships connect the impact of WhatsApp communication on employee performance. The study recommends the use of WhatsApp in the workplace as a safe tool to boost performance and improve productivity and satisfaction.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Using the educational setting of Jordan, this research aims to investigate the complex relationship between teacher-student rapport and student involvement in gamified learning experiences. As it relates to the effective use of gamified learning methodologies, this research digs into the far-reaching ramifications of cultivating strong interpersonal interactions between instructors and students. This research uses a strict quantitative technique to investigate the complex relationships between 400 children and 40 teachers. This study's results shed light on an interesting and statistically significant phenomenon: a significant positive connection (r = 0.742, p 0.001) between teacher-student rapport and the amount of engagement seen in gamified learning sessions. The finding, in line with Jordan's educational reforms, highlights the critical role of positive rapport in generating dynamic and significant participation within modern instructional techniques. The practical repercussions highlight the need for teachers to work to improve their interpersonal skills. It becomes clear that this is a crucial factor in enabling effective teaching and learning, especially within the context of contemporary pedagogical approaches. The current research helps us better understand the complex dynamics at play in teacher-student relationships, illuminating their far-reaching consequences for the pursuit of educational excellence in the Jordann setting.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Education is a fundamental sector in all countries, where in some countries students com-pete to get an educational grant due to its high cost. The incorporation of artificial intelli-gence in education holds great promise for the advancement of educational systems and pro-cesses. Educational data mining involves the analysis of data generated within educational environments to extract valuable insights into student performance and other factors that enhance teaching and learning. This paper aims to analyze the factors influencing students' performance and consequently, assist granting organizations in selecting suitable students in the Arab region (Jordan as a use case). The problem was addressed using a rule-based tech-nique to facilitate the utilization and implementation of a decision support system. To this end, three classical rule induction algorithms, namely PART, JRip, and RIDOR, were em-ployed. The data utilized in this study was collected from undergraduate students at the University of Jordan from 2010 to 2020. The constructed models were evaluated based on metrics such as accuracy, recall, precision, and f1-score. The findings indicate that the JRip algorithm outperformed PART and RIDOR in most of the datasets based on f1-score metric. The interpreted decision rules of the best models reveal that both features; the average study years and high school averages play vital roles in deciding which students should receive scholarships. The paper concludes with several suggested implications to support and en-hance the decision-making process of granting agencies in the realm of higher education.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The advent of technology has dramatically reshaped the ways in which we assimilate knowledge, teach, and access information. From online learning platforms to interactive educational games and virtual reality simulations, technology has transformed the traditional classroom into a vibrant, engaging, and inclusive educational landscape. A notable advancement in artificial intelligence technology is ChatGPT (Generative Pre-trained Transformer), which provides personalized and effective learning experiences by delivering customized feedback and explanations to students. Despite the considerable research on the adoption or acceptance of e-learning, there is a paucity of research on the acceptance and utilization of ChatGPT, highlighting the need for further investigation. This study aims to bridge this gap by proposing an integrated model that incorporates three key constructs: perceived learning value, perceived satisfaction, and personal innovativeness. A questionnaire survey was administered to 289 university students in the United Arab Emirates (UAE), and the data collected were analyzed using the partial least squares-structural equation modeling (PLS-SEM) approach. The results revealed that "perceived learning value, perceived satisfaction, and personal innovativeness" are the most influential and critical determinants of students' intentions to use learning platforms through ChatGPT. This research contributes to the existing body of literature on AI and environmental sustainability, providing invaluable insights for practitioners, policymakers, and AI product developers. These insights can guide the development and implementation of AI technologies to better align with users' needs and preferences, while also considering the broader environmental context.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)