Research on digital literacy, knowledge management and process innovation variables has not been widely carried out in Indonesia, therefore more studies need to be carried out immediately since small and medium enterprises (SMEs) play an important role in economic activities. The purpose of this research is to investigate the effect of digital literacy on knowledge management, digital literacy on process innovation and financial management on process innovation. The research method is quantitative using partial least square structural equation modeling (SEM) analysis with data analysis tools using SmartPLS 3.0 software. The study involved 489 respondents who owned SMEs and it was determined using simple random sampling. The type of variable scale used is the ordinal scale. The rating scale for each statement uses a rating scale technique with a Likert scale type. Online questionnaires are distributed through online media, the data analysis stage is the outer model test, namely the validity and reliability test and the inner model test, namely the hypothesis test or significance test. The independent variable of this research is digital literacy, the mediating variable is knowledge management, and the dependent variable is process innovation variable. Based on the results of research data analysis it was found that digital literacy had a positive and significant relationship on knowledge management, digital literacy had a positive and significant relationship on process innovation, knowledge management had a positive and significant relationship on process innovation. Knowledge management played as full mediators in the relationship between digital leisure variables and process innovation.

This research investigates the interplay between public administration, educational socialization on social media, population literacy awareness, and public satisfaction in the context of population services. The primary objective is understanding how these variables are interconnected and their collective impact on public satisfaction. The study employs a quantitative approach, collecting data through structured questionnaires from a randomly selected sample. Data analysis involves various statistical techniques using Smart PLS, including regression and mediation analysis. The findings reveal that public administration significantly influences population literacy awareness, underscoring the role of government agencies in shaping citizen understanding of demographic policies. While it was anticipated that population literacy awareness would mediate the relationship between public administration and educational socialization on social media for public satisfaction, this mediating effect needed to be supported. However, social media use was found to influence population literacy awareness, indirectly affecting public satisfaction directly. It highlights the potential of digital platforms to enhance citizen understanding and engagement. The implications are substantial. Governments should recognize the importance of effective communication and digital engagement in fostering an informed and satisfied citizenry. Additionally, tailored communication and education initiatives are crucial for promoting public understanding and engagement, ultimately contributing to higher levels of public satisfaction. The research's novelty lies in its exploration of the complex dynamics among these variables and its focus on the role of digital platforms in enhancing population literacy awareness. However, some limitations include the potential for context-specific findings and the need for further research in diverse settings.

Social media has proven to be quite effective in raising awareness and anti-corruption movements in society. This research aimed to analyze the use of social media Twitter as a means of the Corruption Eradication Commission (KPK) in conducting anti-corruption campaigns in Indonesia. The research employed a qualitative content analysis on the KPK's official Twitter account. The data were processed using the NVIVO 12 Plus software to answer research questions. This research revealed that the KPK's Twitter account is quite active in carrying out anti-corruption campaign activities, although in general it is not optimal. It can be seen from the low intensity of communication and limited communication network so that it is considered as less collaborative. Improving the problems is needed by KPK as it must also show good performance so that public trust continues in high condition. However, this research has limitations in looking at all anti-corruption campaigns carried out by the KPK because it only used Twitter as the reference. Therefore, further research is suggested to analyze all KPK social media such as Youtube and Instagram.

Educational systems worldwide have witnessed a significant shift towards technological applications, especially after COVID-19, which impacted how the learning contents are delivered in classrooms. Given the increased attention given to the numerous advantages of computer Simulations (CSs) programs, particularly in science education, this study compared the efficacy of employing a lab simulation of Newton's Second Law of Motion to teach physics in the UAE secondary school environment versus the more conventional approach (Face-to-face instruction). The study employed a quasi-experimental design that included 90 UAE 11th-grade students from two public schools in the City of Al Ain. The intervention included student engagement in the PhET interactive simulation of Newton’s second law of motion. The study employed the Test of Science-Related Attitudes (TOSRA) questionnaire to collect data before and after the intervention for the experimental and control groups. The findings demonstrated statistically significant differences between experimental and control groups in students' attitudes toward scientific inquiry, enjoyment of science lessons, and career interest in physics/science. Furthermore, results showed a significant difference in attitudes perceived in these scales, with males having a more significant effect size than female students in all three scales. The study concludes with implications and suggests recommendations for future research and practice.

Unequal development is a major factor in measuring Indonesia's poverty problem, resulting in areas that are left behind. It is a primary concern of the government and stakeholders since it is unresolved and will lead to more problems in the community. Therefore, the government and stakeholders conduct various village developments to prosper the community. One is Batik village in Kemang, Bogor Regency, Indonesia. The Pakuan University of Bogor initiated the village development program. The collaboration forms a communication network and communication patterns to facilitate the delivery of messages. This study aims to identify and analyze the communication network pattern of stakeholders in the development of Kampung Batik in Kemang, Bogor Regency, Indonesia. This study is designed using a qualitative approach through interviews with relevant stakeholders. The communication network was analyzed using Sociometric Analysis through UCINET VI. The result indicates that the relationship between actors in the development of Kampung Batik is 75.5 percent and categorized as quite strong. Also, the communication pattern formed is an all-channel pattern with five actors who act as the star, bridge, opinion leader, liaison, cosmopolite, and isolate. This model supports the smart economy's potential to develop a smart village.

Islamic banking across the developing countries may undoubtedly become more prevalent thanks to financial technology, making it more competitive in the financial sector. The current study's goal is to extensively address fintech on Islamic banks and to examine the effect of fintech Services upon Islamic banking financial performance around Jordan. The investigation utilized a quantitative-descriptive survey approach. The study utilized annual data (panel data) which were acquired via financial institutions figures of the annual statements from the Jordan's Islamic Bank (JIB) registered with Amman Stock Exchange from 2017 to 2021. This investigation found Fintech services, such as internet banking, mobile banking, crowdfunding, and automated teller machines had a substantial effect on JIB's financial performance. The positive beta value suggests that there were favorable relationships among JIB's financial success from 2017 to 2021 on Fintech services. Finally, the study recommends that JIB increase its efforts to inform the public concerning Islamic banking services.

The accelerated progress of Artificial Intelligence (AI) within the accounting field has resulted in a heightened use of this technology in international enterprises, therefore generating noteworthy ethical concerns. This research investigates the ethical implications that arise from the use of AI in accounting practices, focusing on international corporations operating in Jordan. The objective of this research is to provide a comprehensive framework for the ethical and responsible integration of AI within the accounting domain. The research used a survey methods approach while 379 respondents were selected using cluster and proportional sampling. The qualitative component of the research investigates the viewpoints and concerns of persons pertaining to the use of AI. The study results provide significant contributions to the development of a context-specific paradigm for AI ethics that prioritizes concepts such as transparency, fairness, and accountability. The findings of this study have substantial value for multinational corporations engaged in commercial operations in Jordan and similar regions. The results provide organizations with the necessary tools to proficiently address the ethical dilemmas that emerge as a result of using artificial intelligence in accounting procedures.

China is the largest emitter of greenhouse gases globally, responsible for a substantial portion of the world's total carbon dioxide emissions. Many researchers investigated this issue; however, the literature is silent on how FinTech-based incentives can improve environmental performance. The research aims to shed light on the complex relationships among FinTech incentives, green consumer behavior, environmental consciousness, and environmental performance. Data was collected from 380 respondents representing diverse roles in the manufacturing industry. We used Smart-PLS and SPSS to test our hypothesis. The results confirm a positive relationship between FinTech incentives and green consumer behavior. However, consumer demographics and environmental awareness do not significantly moderate this relationship. The mediation analysis reveals that green consumer behavior mediates the relationship between FinTech incentives and environmental performance, while environmental consciousness mediates the relationship between FinTech incentives and green consumer behavior. Additionally, green consumer behavior mediates the relationship between environmental consciousness and environmental performance. The study's findings suggest that FinTech incentives effectively encourage eco-friendly choices, positively influencing environmental performance. This research contributes valuable insights for policymakers and businesses seeking to design effective environmental strategies and promote sustainability in the manufacturing industry. By leveraging FinTech incentives to encourage eco-friendly choices and foster environmental consciousness, businesses can contribute to a more sustainable future, aligning with global efforts to address environmental challenges and foster responsible consumption patterns in China and beyond.

The security and integrity of computer systems and networks highly depend on malware detection. In the realm of malware detection, the K-Nearest Neighbors (KNN) algorithm is a well-liked and successful machine learning algorithm. However, the choice of an acceptable distance metric parameter has a significant impact on the KNN algorithm's performance. This study tries to improve malware detection by adjusting the KNN algorithm's distance metric parameter. The distance metric greatly influences the similarity or dissimilarity between instances in the feature space. The KNN algorithm for malware detection can be more accurate and effective by carefully choosing or modifying the distance metric. This paper analyzes multiple distance metrics, including Minkowski distance, Manhattan distance, and Euclidean distance. These metrics account for the traits of malware samples while capturing various aspects of similarity. The effectiveness of the KNN algorithm is evaluated using the MalMem-2022 malware dataset, and the results are broken down into these three-distance metrics. The experimental findings show that, among the three distance metric parameters, the Euclidean and Minkowski distance metric parameters considerably produced the best outcomes with binary classification. While with multiclass classification, the KNN algorithm has achieved the highest outcomes using Manhattan distance.

Given the widespread adoption of social media as a primary information source, organizations can no longer do without it. The importance of social media in creating sustainable company strategies has increased in tandem with the public's growing knowledge of sustainability issues. This study examines how marketing and social media can create brand sustainability plans. To create a practical framework for creating sustainability strategies, the relevant literature was evaluated. Market managers and digital marketers were surveyed using an online questionnaire. To extract conclusions from the data and model variables, a structural equation model was used. Findings from the survey indicate that businesses are increasingly turning to social media to share information with stakeholders, solicit opinions, and collect information for use in developing sustainability plans. Market managers play a vital role in ensuring the sustainability of their businesses. The research has theoretical and managerial implications.