The impact of teacher leadership and curriculum on the effectiveness of learning technology utilization and the quality of e-learning has been proven by research. The study included 165 samples of teachers from Halang Island, Riau, Indonesia. Respondents are certified teachers with a minimum of ten years of experience, as determined by the purposive sampling method. Respondents completed a research questionnaire, which was used to collect data. Data ws proceeded with Smart PLS software, including validity, reliability, and hypothesis testing. The study's findings demonstrated that teacher leadership and curriculum directly impacted the effectiveness of learning technology utilization. The quality of e-learning was directly influenced by teacher leadership, curriculum, and the effectiveness of learning technology utilization. Finally, teacher leadership and curriculum impacted e-learning quality through the effectiveness of learning technology utilization. This study suggests two points. First, if you want to improve the effectiveness of learning technology utilization, the policy priority should be to update and then improve teacher leadership. Second, increasing the effectiveness of learning technology utilization is a policy priority if you want to improve the quality of e-learning. It was followed by curriculum updates and increased teacher leadership.

The paradigm shift in local government financial management necessitates a change in the perspective of government officials, viewing them as financial managers. This study explores the intriguing aspect of assessing managerial performance, particularly in government organizations. The uniformity in reward structures, such as salary and benefits, irrespective of different workloads, adds to the interest in this investigation. To analyze these factors, a quantitative approach with Partial Least Squares (PLS) as an analytical tool and path analysis for mediation examination is employed. The target population for this study comprises employees from the planning division of the Central Sulawesi Government. A saturated sample is used as the sampling technique. Data collection involves distributing 180 questionnaires to gather relevant information. The results of this study reveal several important findings. Firstly, it tests the hypothesis that electronic participatory budgeting does not have a direct effect on work tension. Secondly, it demonstrates that budget emphasis has a direct effect on work tension. Thirdly, it concludes that work tension does not have a direct effect on managerial performance. Additionally, the study indicates that job tension does not mediate the effect of electronic participatory budgeting on managerial performance. However, work tensions are found to mediate the influence of budgetary emphasis on managerial performance.

This study investigates the factors that influence the sharing of information on social media platforms and examines the effects of perceived security, perceived privacy, and user awareness on users' trust in social media platforms, as well as the moderating effects of age, gender, educational attainment, and internet proficiency on information sharing. The study collected data from 837 social media users in Jordan and analyzed them using structural equation modeling (SEM), confirmatory factor analysis (CFA), and machine learning (ML) methods. The findings of the study indicate that perceived security, perceived privacy, and user awareness all have a significant impact on users' trust in social media platforms. Trust, in turn, has a significant impact on the amount of information shared on these platforms. Also, the findings of this study provide valuable insights into the dynamics of information sharing on social networks. This knowledge will be of interest to managers, policymakers, and developers of social media platforms. In addition, the findings of the study also have implications for the privacy and security of social media users. For example, social media users can be more careful about the information they share on social media platforms, and they can take steps to protect their privacy.

This study set out to find out on how big data analytics, workload, work wages, and organizational structure pressures affect employee job performance and overall business performance in the Jordan banking sector in the context of that country's banking sector. 292 samples from the research study were collected, analyzed, and debated to test the study's hypotheses. Employee and company success were found to be affected by workload, compensation, and organizational structure. Workload was reflected by job completion rate, average daily issues, and work completion time, while big data was reflected by external and internal, unique application, indexing, and source correctness. Work compensation, including employee compensation, employee experience and skill, and employee incentives and rewards, is the third primary factor. Communities of practice, group work, and physical infrastructure make up the fourth and last important factor, the organization's structure. The study finds that when dealing with large amounts of data, reducing the workload can improve employee performance, increasing employee motivation through higher wages and bonuses can improve performance, and having an organizational structure that promotes teamwork and work teams can improve employees' abilities to solve problems and improve work performance, which in turn affects overall productivity. This study contributes fresh information to an emerging field that requires more investigation to fully understand the interplay between big data, workload, work wages, and organizational structure pressures. The topic of this study, the Jordan banking sector, is both innovative and highly relevant because it may help financial institutions enhance their operations and provide superior customer service.

The goal of this study is to evaluate the way digital marketing (DM) works in increasing customer satisfaction (CS) and brand loyalty (BL) at the Saudi Arabian Restaurants. The study uses 7 variables for analysis such as Service quality satisfaction (SQS) Digital engagement satisfaction (DES) Recommendation Likelihood (RL) Digital Promotions (DP) Online Presence Perception (OPP) Promotions Effectiveness (PE) Social Media Engagement (SME). Data from customers using digital media has been gathered through questionnaires. 410 respondents provided the data, which was then examined using SPSS and AMOS. The study will give management the knowledge they need to modify procedures and train employees in order to satisfy customers and promote BL. Future research can be done across several corporate sectors and cultural contexts. The premise for this study is provided by this paper, which also offers managers useful guidance regarding how to train employees to increase consumer satisfaction and BL.

This research aims to present the Hybrid SSA-TBATS approach as an alternate forecasting technique that does not need specific assumptions or requirements such as stationarity, linear or nonlinear process, and normality. This analysis used Indonesian exports (in millions of USD) from January 1993 to July 2022. The findings of this research reveal that the Hybrid SSA-TBATS method outperforms SSA and TBATS in forecasting accuracy and defines the window length and number of groups. Therefore, it is highly recommended based on MAPE since it does not need any information on the characteristics of the data to be forecasted.

Thanks to technological advancements in finance, Islamic banking might surely spread throughout developing nations and become more viable in the financial industry. The present investigation aims to thoroughly explore the impact of fintech upon Islamic banks and also investigate how fintech facilities affect Islamic banks performance within Jordan. A strategy known as a quantitative-descriptive inquiry was used in the inquiry. This study made use of yearly data (a panel data) that was collected from banking organizations using statistics based on yearly reports provided by Jordan Islamic bank, Safwa Islamic Bank and International Arab Islamic Bank listed alongside the Amman Stock Exchange between 2017 and 2021. The study discovered that financial performance of Islamic Banks was significantly impacted by Fintech services including online banking along with mobile banking. The increased beta value predicts that between 2017 to 2021, the financial prosperity of Arab Islamic International Bank, Jordan Islamic Bank, and Safwa Islamic Bank would be positively correlated with Fintech services. Additionally, it was discovered that SMS Financing and crowdsourcing had a detrimental impact on Islamic Banks financial performance. The investigation concludes by recommending that Islamic banking included in the study step up their attempts to educate the public about Islamic banking facilities.

This study is done to identify the impact of promotion on the purchase intentions of video games in Jordan. The independent variables used to test promotion were trailers, discounts, influencers/streamers, and social media. The data were collected by using a survey designed on google forms sent or using a Quick Response (QR) code to random gamers in Jordan. 129 people responded to the survey. The data were coded on SPSS and reliability, validity, and correlation among variables were confirmed, then the hypotheses were tested by multiple regressions. The researcher found a statistically significant impact of promotional tools on purchase intentions of the video gaming industry in Jordan, where trailers have the highest significant positive effect on purchase intentions, followed by social media, then influencers/streamers, while discounts do not significantly affect purchase intentions of video games in Jordan. Some limitations and recommendations for future research have been provided at the end of the research.

Dental caries is arguably the most persistent dental condition that affects most people over their lives. Carious lesions are commonly diagnosed by dentists using clinical and visual examination along with oral radiographs. In many circumstances, dental caries is challenging to detect with photography and might be mistaken as shadows for various reasons, including poor photo quality. However, with the introduction of Artificial Intelligence and robotic systems in dentistry, photographs can be a helpful tool in oral epidemiological research for the assessment of dental caries prevalence among the population. It can be used particularly to create a new automated approach to calculate DMF (Decay, Missing, Filled) index score. In this paper, an autonomous diagnostic approach for detecting dental cavities in photos is developed using deep learning algorithms and ensemble methods. The proposed technique employs a set of pretrained models including Xception, VGG16, VGG19, and DenseNet121 to extract essential characteristics from photographs and to classify images as either normal or caries. Then, two ensemble learning methods, E- majority and E-sum, are employed based on majority voting and sum rule to boost the performances of the individual pretrained model. Experiments are conducted on 50 images with data augmentation for normal and caries images, the employed E-majority and E-sum achieved an accuracy score of 96% and 97%, respectively. The obtained results demonstrate the superiority of the proposed ensemble framework in the detection of caries. Furthermore, this framework is a step toward constructing a fully automated, efficient decision support system to be used in the dentistry area.

The main objectives of this research are to identify significant spatial and temporal components associated with diarrhea and provide an accurate forecast. Using data from the Ban-dung city health surveillance system, the analysis reveals a decreasing trend in both the number of incidences and the estimated relative risks of diarrhea in most districts. Key factors contributing to diarrhea variation include temporally structured, spatially structured, and unstructured effects of space-time interaction Type I. No clear seasonal pattern is observed in diarrhea incidence among children under five, emphasizing the need for consistent vigilance and preventive measures. Spatial clustering was observed in the eastern and western parts of Bandung city. The forecasting model predicts a continued decline in diarrhea incidence and relative risk throughout 2022.