As the complexity of modern web applications continues to increase—particularly with the rise of Single-Page Applications (SPAs)—the need for effective monitoring mechanisms becomes more critical to support fast and accurate debugging processes. One promising approach is the implementation of a monitoring system based on Database Management Systems (DBMS), which allows for systematic logging and tracking of execution data within the application’s runtime environment. This study aims to explore the role of DBMS in supporting bug reproduction, a process that involves recreating a previously encountered bug by collecting real-time information such as activity logs, event traces, and environmental variables. The research method includes the development of a monitoring prototype integrated into a web application, where all runtime data is stored in a centralized database. Experimental evaluations were conducted on large-scale web applications to assess the system’s effectiveness in detecting and reproducing bugs. The results indicate that DBMS-based monitoring significantly improves debugging efficiency by providing contextual execution data that would otherwise be undocumented. Case studies involving the implementation of database systems like MySQL and SQLite in mobile applications demonstrated improvements in both reliability and data access speed for log management. These findings show that integrating monitoring with DBMS contributes meaningfully to maintaining software quality. However, this integration also introduces technical challenges, such as heavy logging loads, potential latency, and data security concerns. To address these issues, this study recommends optimization strategies including caching mechanisms, asynchronous I/O operations, and the adoption of cloud-native architectures to enhance system scalability and performance. By applying these approaches, bug reproduction can be performed more quickly, accurately, and efficiently—ultimately supporting the development of robust and reliable web applications in today’s digital era. This research highlights the importance of runtime observability and structured monitoring as key elements in modern software maintenance and debugging workflows. 

The purpose of this study is to investigate how customers' purchasing decisions at Abu Rohmah Store are influenced by store layout and rational motivation. The study uses a quantitative survey approach, gathering information from 50 respondents via questionnaires. Multiple linear regression analysis was used to examine the gathered data. The results indicate that store layout has a significant effect on consumers' purchasing decisions, with a regression coefficient of 0.814. Furthermore, customers' rational motivation is also significantly influenced by store layout, as evidenced by the regression coefficient of 0.347. According to the coefficient of determination, 64% of the variation in consumers' purchase decisions can be explained by these two variables. These results aid in the creation of marketing plans and the enhancement of offerings in the neighborhood retail industry.

This study aims to examine the efforts in human resource (HR) planning and development to enhance productivity and work effectiveness at Suzuki Company, Sutomo Branch. Well-structured HR planning and competency development strategies are considered crucial factors in supporting the achievement of operational targets and improving overall company performance. The research adopts a descriptive qualitative approach with data collected through interviews, observations, and document analysis. The findings indicate that continuous training programs, regular performance evaluations, and structured career management have a positive impact on employee motivation and operational efficiency. Therefore, focused and consistent HR planning and development are essential strategies for creating competitive advantages amidst the increasingly intense competition in the automotive industry.

This study aims to analyze the effect of service quality and price on consumer satisfaction in Grab online transportation services in Bogor City. The study uses a quantitative approach with a survey method, involving 63 respondents who are active Grab users. Data were obtained through a structured questionnaire and have been tested for validity and reliability. The data analysis process was carried out using multiple linear regression to identify the simultaneous and partial effects between independent variables, namely service quality and price, on the dependent variable, namely consumer satisfaction. Prior to analysis, classical assumption tests were conducted including multicollinearity, heteroscedasticity, and normality tests to ensure the accuracy of the regression model. The results of the study indicate that service quality and price significantly affect consumer satisfaction both simultaneously and partially. This emphasizes the importance of improving service quality and determining competitive prices to maintain consumer loyalty. This study provides insights for Grab management and other online transportation sectors to optimize consumer experience-based marketing strategies. By focusing on consumer needs and improving operational aspects, companies can increase their competitiveness in an increasingly competitive market.

Public economic policy is a crucial instrument in addressing various forms of market failure, such as negative externalities and income inequality. In this context, government intervention through taxation, subsidies, and redistribution serves as a strategic step to achieve a balance between economic efficiency and social equity. This article aims to examine the role of public economic policy in correcting the impact of externalities and reducing the gap in income distribution. Using a qualitative descriptive approach and literature study method, the results show that Pigovian taxes, subsidies for positive sectors, progressive tax systems, and data-based redistribution programs are key pillars in building a fairer and more inclusive economic system.

Public economic policy plays a crucial role in balancing market efficiency and social justice. This article aims to analyze how optimizing public policy can address major challenges such as negative externalities, limitations in public goods provision, income inequality, and unfair taxation systems. This study employs a qualitative approach through literature review focusing on recent academic works. The findings suggest that data-driven and holistic economic public policies can significantly contribute to enhancing social welfare and promoting inclusive economic growth. Strengthening implementation and fostering cross-sector collaboration are essential to ensure more targeted and sustainable policy outcomes.

This study aims to understand the influence of content marketing and influencer marketing on otak-otak purchasing decisions in Bintan Regency. The method used is a quantitative survey with online data collection via Google Form to 59 respondents aged 15-40 years who have consumed otak-otak in the area. Data were analyzed using SPSS software based on consumer behavior theory and the AIDA model, which focuses on how content and influencers can influence purchasing interest.The results of the study show that content marketing and influencer marketing significantly influence otak-otak purchasing decisions. Interesting content and trust in influencers can increase consumer interest and desire to buy the product. This finding shows the importance of the right digital marketing strategy in supporting local MSMEs to be able to compete and increase sales of regional products.However, this study has limitations in small samples and is limited to certain areas, so the results do not represent the entire population of otak-otak consumers in Bintan Regency. However, this study provides a practical contribution for MSME actors and local marketers to design more effective and targeted digital marketing strategies. Academically, this study enriches the study of digital marketing and consumer behavior in the local food industry.

This study aims to examine the influence of product variation and service quality on consumer satisfaction at Kedai Kopi Tilik Sawah in Kediri City. The growth of the coffee shop industry in Indonesia, including in Kediri City, shows a positive trend along with the increasing interest of the public, especially young people and workers, who use coffee shops as places to relax, study, and work. Kedai Kopi Tilik Sawah has become a popular destination due to its open concept and natural, comfortable atmosphere. The research method used is a quantitative approach by distributing questionnaires to 100 respondents selected through purposive sampling. The data were analyzed using multiple linear regression with SPSS version 25 software. The results show that product variation and service quality have a positive and significant effect on consumer satisfaction, both partially and simultaneously. These findings emphasize the importance of managing diverse products and quality services in building customer loyalty. The implications of this study can serve as a reference for coffee shop managers in designing more effective marketing strategies to face the increasingly competitive local culinary industry.

The key measure of employee performance productivity is determined by several factors, such as appropriate age, employee attendance rate (infrequent illness or leave), and the number of non-effective working days. To determine the extent to which these factors influence employee productivity, multiple linear regression analysis is used. The results of the analysis show that employee age has a significant influence on productivity, while non-effective working days and the frequency of employee illness or leave have little impact.

This study aims to analyze the potential of superior commodities in North Tapanuli Regency, especially pineapple commodities, using the Location Quotient (LQ) method. North Tapanuli Regency is known to have abundant agricultural resources, but not all of them have been optimized for export purposes. In this study, secondary data in the form of GRDP in 2024 from BPS was used as the basis for calculating LQ to identify the base sector. The results of the study showed that of several agricultural sub-sectors, pineapple fruit commodities had the highest LQ value of 7.89, which indicated that pineapple has a comparative advantage and is very potential to be developed as an export product. To support the development of this commodity, a SWOT analysis was conducted on two main processed products, namely pineapple dodol and pineapple chips. This analysis shows that pineapple is not only superior in terms of production quantity, but also has great potential to be developed into high value-added products. These findings provide an important contribution to the strategy for developing local commodities that are export-oriented and support sustainable regional economic development.