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The food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

This research aimed to examine how financial literacy and the use of digital payment systems impact students' financial behavior in the Tasikmalaya area. Although digital wallets are widely used for transactions, many students do not realize that this ease of access can shape their financial habits. Often, e-wallets are seen purely as convenient tools, without acknowledging their influence on spending patterns and money management. A quantitative method was employed, with data gathered via questionnaires distributed to 140 student respondents. The findings show that financial literacy significantly affects financial behavior on its own, while e-wallet usage does not have a notable individual impact. Nevertheless, when both variables are analyzed simultaneously, they significantly influence financial behavior. These outcomes are consistent with the Theory of Planned Behavior, which explains that personal attitudes, control over behavior, and habits collectively contribute to financial decisions.Based on these results, the study suggests that improving financial literacy is crucial so that students can make more informed decisions and manage their finances wisely when using digital wallets.

Macroeconomic uncertainty poses a structural challenge for the sustainability of micro, small, and medium enterprises (MSMEs) in Indonesia. Fluctuations in inflation, benchmark interest rates, and exchange rates have a direct impact on liquidity, cost structures, and investment decisions. This study aims to explore the types of financial strategies adopted by MSMEs in response to macroeconomic pressures using a systematic literature review and secondary data analysis covering the period from 2019 to May 2024. Data were sourced from official national institutions, including the Central Bureau of Statistics, Bank Indonesia, the Ministry of Cooperatives and MSMEs, as well as relevant academic literature. The findings reveal that MSME financial strategies can be categorized into three key domains: cash management, cost control, and investment planning. MSMEs employing flexible strategies—such as increasing cash buffers, reducing operational costs, and diversifying products or financing sources—demonstrate higher resilience in the face of economic volatility. This study contributes theoretically by enriching the framework of financial adaptation for MSMEs and practically by informing financial literacy programs and policy design. The study also acknowledges limitations in the use of aggregate secondary data and recommends that future research adopt a mixed-method approach to capture undocumented informal financial practices at the grassroots level

Burn injuries are complex tissue damage often accompanied by serious complications such as infection, systemic inflammation, and organ dysfunction. Effective burn management requires a comprehensive multidisciplinary approach, including infection control, local wound care, nutritional support, and regenerative therapy. Along with advances in science and technology, various novel treatment modalities have been developed to accelerate healing, reduce scarring, and improve patients’ quality of life. This study aims to evaluate the effectiveness and clinical prospects of the latest burn treatment modalities through a review of relevant literature from 2021 to 2025. This research employed a descriptive qualitative literature review method, analyzing 10 relevant scientific articles obtained from academic databases such as PubMed, ScienceDirect, and Google Scholar. The reviewed modalities include stem cell therapy, Platelet Rich Plasma (PRP), silver nanoparticles, nanofiber and hydrogel-based dressings, natural extracts such as aloe vera and binahong, as well as advanced technologies like smart dressings and low-level laser therapy. The results indicate that regenerative and smart technology-based approaches significantly enhance epithelialization, reduce infection, and improve tissue repair. Natural therapies also show promising potential as safe, affordable, and effective treatment alternatives. In conclusion, the integration of biological therapy, phytotherapy, and modern technology represents a promising direction in contemporary burn care. Further large-scale clinical research is needed to confirm the long-term safety and effectiveness of each modality.

Financing in the health sector plays an important role in ensuring the sustainability of hospital operations and the provision of quality health services. Structured and efficient financing planning contributes greatly to improving the health of the community. However, in practice, it is not uncommon to find problems due to weak financial planning, such as budget limitations that have an impact on the low quality of health services and waste due to inappropriate spending. To overcome these problems, strategic steps are needed, including through increasing funding, more accountable management and allocation of funds, and controlling service costs. Thus, the issue of health financing has a significant influence on the quality of public health and is an important part of the development of the national health system.

Enterprise Resource Planning (ERP) systems have become the operational backbone of many modern companies, not only as a data integration tool but also as a crucial pillar in management control systems (MCS). This study aims to comprehensively analyze the impact of ERP implementation on operational efficiency and corporate accountability. Using a qualitative approach through literature study and case review, this study explores how ERP facilitates real-time and integrated information flow, which in turn improves managerial decision-making capabilities, resource optimization, and increased transparency and accountability at various levels of the organization. The results show that ERP contributes significantly to increased efficiency through process standardization and reduced redundancy, and strengthens accountability by providing clear audit trails and reliable data. However, the success of the implementation is highly dependent on factors such as top management support, adequate employee training, and alignment with business strategy.  

This study investigates the factors influencing accountability in the management of village funds by local governments in Kangkung District, Kendal Regency. The research is driven by the growing number of village fund mismanagement cases in Indonesia, highlighting the urgent need for improved governance. Key variables examined in this study include the use of the siskeudes application, staff competence, transparency, internal control systems, local wisdom, and organizational commitment. A quantitative approach was employed, with data gathered through questionnaires distributed to 63 respondents comprising village officials, BPD members, and community representatives. The results are expected to provide both theoretical contributions to the field of public sector accounting and practical insights for village governments to enhance financial accountability and transparency. Ultimately, the study aims to support the development of sustainable and participatory village governance.

This study aims to analyze how the elements of the Fraud Triangle, namely pressure, opportunity, and rationalization, influence the occurrence of financial statement fraud. Using a qualitative method with a descriptive approach and secondary data sources from relevant literature published in 2020–2025, this study examines various previous research findings related to the application of the Fraud Triangle theory in the industrial sector in Indonesia and internationally. The study results indicate that pressure, especially in the form of high financial targets and external pressure, is the dominant factor that triggers management to manipulate reports. Meanwhile, opportunity does not always have a significant impact on fraud due to the presence of effective internal control systems and external supervision. Rationalization has been proven to also drive fraudulent actions through moral justification by the perpetrators. This study concludes that the Fraud Triangle remains a relevant conceptual framework in understanding and detecting potential financial statement fraud, as well as providing implications for improving corporate governance and control systems.  

Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

This study aims to analyze hazard identification in order to improve operational safety aspects in the service road area of I Gusti Ngurah Rai International Airport, Bali. This area is a vital part of the airside that has a high level of activity and complex safety risks, thus requiring special attention to potential hazards that may arise. The research method used is a qualitative descriptive approach, with data collection techniques through direct observation in the field, in-depth interviews with related personnel, and documentation studies relevant to the airport's safety system and operational procedures. The results of the study indicate that there are still significant potential safety risks in the service road area. Some key findings include haphazard parking practices by Ground Support Equipment (GSE), undisciplined behavior of ground handling personnel, and passenger movement in the operational area without adequate officer supervision. These problems are largely caused by weak supervision from the Apron Movement Control (AMC) unit, as well as the low level of understanding and implementation of safety culture among field workers. Through the process of identifying and assessing risks using the Hazard Identification and Risk Assessment (HIRA) approach, researchers succeeded in mapping the severity of risks and developing appropriate mitigation measures, such as regulating GSE parking procedures, improving safety training, and adding supervisory personnel at vulnerable points. It is hoped that the findings of this study can be a basis for consideration for the management of I Gusti Ngurah Rai International Airport, Bali, in formulating policies and strategies for improving operational safety as a whole, especially in implementing a more effective and sustainable Safety Management Sistem (SMS).  

This study examines the influence of leverage, profitability, and capital structure on earnings management in consumer non-cyclicals companies listed on the Indonesia Stock Exchange (IDX) during the period 2019–2023. Earnings management has become a central issue in financial reporting, as it reflects managerial discretion in presenting financial information that may not fully align with the company’s actual economic condition. Understanding the determinants of earnings management is therefore essential to enhance transparency, credibility, and stakeholder trust in corporate financial reports. The research employed a quantitative approach using multiple linear regression analysis, with data processed through SPSS version 25. The sample consisted of 104 company-year observations, which were selected using purposive sampling techniques and subsequently refined through outlier testing to ensure data validity and reliability. The independent variables analyzed were leverage, profitability, and capital structure, while earnings management served as the dependent variable. The empirical findings demonstrate that leverage and profitability exert a significant influence on earnings management practices. Specifically, companies with higher leverage tend to engage in earnings management as a mechanism to meet financial obligations and reduce the risk of violating debt covenants. Similarly, higher profitability motivates managers to manipulate earnings in order to sustain investor confidence and maintain a favorable corporate image. In contrast, capital structure is found to have no significant effect on earnings management, indicating that financing decisions between debt and equity may not directly influence managerial behavior in financial reporting. These results highlight the importance of monitoring leverage and profitability indicators as potential predictors of earnings management. For corporate management, the findings suggest the need to implement stronger internal control systems and uphold ethical financial practices. For investors and regulators, the study provides useful insights into assessing company performance beyond reported earnings, thereby supporting more informed decision-making and promoting the integrity of capital markets.

The integration of autonomous systems in traffic management has become increasingly important as urban populations and vehicle numbers continue to rise, leading to significant congestion. Traditional traffic signal control systems, which rely on fixed timing, are no longer sufficient to handle the dynamic and complex nature of urban traffic. To address these challenges, the proposed explainable Deep Reinforcement Learning (DRL) framework aims to optimize traffic signal control by dynamically adjusting traffic signals based on real-time data. This approach enhances traffic flow efficiency, reduces congestion, and improves overall system performance. The framework leverages Vehicle-to-Everything (V2X) communication, which enables real-time data exchange between vehicles, infrastructure, and other road users, extending the perception range of autonomous vehicles and providing valuable insights for traffic signal optimization. Additionally, the integration of smart infrastructure, such as smart intersections, plays a crucial role in enabling adaptive traffic management and facilitating better coordination across multiple intersections. One of the key advantages of the proposed system is its transparency, achieved through the implementation of explainable AI (XAI) techniques. These mechanisms provide clear insights into the decision-making processes, ensuring that traffic management authorities and system users can understand the rationale behind the system’s decisions. Although challenges such as data accuracy, scalability, and cybersecurity risks remain, the proposed DRL framework shows great promise in revolutionizing traffic management systems. Future research directions include enhancing data collection methods, improving the scalability of the system for larger cities, and further developing explainability features to improve trust and adoption in real-world applications.

Late payment of accounts receivable is a serious challenge that can disrupt the stability of the company's cash flow and financial performance. This study aims to evaluate the role of risk management in minimizing late payment of accounts receivable at PT Alam Mulya, a logistics company in Surabaya. The research method used is descriptive qualitative with a case study approach, through direct observation, interviews, and documentation during the five-month internship period. The results showed that the company has implemented risk management principles, such as customer identification, setting credit limits, monitoring maturity, and implementing active collection. However, the implementation has not been thorough and consistent, especially in the aspects of using digital systems, documenting credit policies, and applying sanctions for late payments. It was also found that decision interventions based on personal relationships hindered the effectiveness of risk control. This study recommends the implementation of an integrated digital system, the establishment of a written credit policy, and staff training related to risk management and collection. By strengthening comprehensive risk management, the company is expected to improve the efficiency of receivables management and maintain optimal cash flow sustainability.

In the current era of globalization and technological advancement in business, information systems play a critical role in driving organizational growth. A company’s success heavily relies on an efficient information system capable of providing accurate, timely, and relevant information. This study aims to design a web-based asset management information system to enhance asset management efficiency at PT Wisessa Consulting Indonesia. Asset management is a vital function that must be carried out to monitor the condition and status of assets. The main problems identified include the lack of integration in asset recording and the absence of a user access control system differentiated by role. The system development follows the Waterfall model, which consists of requirements analysis, system design, implementation, testing, and maintenance phases. The developed system manages detailed asset master data, schedules asset maintenance, and regulates user access rights based on roles—namely admin, IT support admin, IT support, manager, and branch user. The implementation results indicate that the system facilitates more accurate and structured asset recording, monitoring, and reporting processes. Furthermore, the system improves asset management effectiveness, ensures data transparency, reduces errors from manual processes, and supports data-driven strategic decision-making within the organization.

Manual stock management systems are still commonly used in electrical equipment sales businesses, often leading to problems such as inaccurate data recording, delayed reporting, and potential data loss. To overcome these issues, a web-based inventory management information system was developed to automate the recording of incoming goods, outgoing goods, damaged items, and lost items. A case study was conducted at Toko Dhanisa Mandiri Jaya, which previously relied on manual bookkeeping using physical logs. The system was developed using the Waterfall method, involving stages such as requirements analysis, system design, implementation, testing, and maintenance. Data collection was carried out through observation, interviews, and literature review. The system includes key features such as inventory data management, transaction processing, reporting, and user management. The implementation results indicate improved operational efficiency, reduced recording errors, and the availability of real-time inventory data to support managerial decision-making. This system is expected to help the store modernize its business processes with better accuracy and control.

Efficient budget management in the public sector requires reliable and relevant information. In this context, management accounting plays a crucial role not only as a financial recording tool but also as a support system for planning, controlling, and evaluating organizational performance. This article explores how management accounting can be implemented to help government institutions and non-profit organizations use public resources effectively. The study uses a descriptive qualitative approach by reviewing relevant academic literature. Findings indicate that a well implemented accounting system can enhance transparency, improve accountability, and reduce waste as well as the risk of budget misuse. Moreover, the financial and non-financial information it provides supports data-driven decision-making processes. Successful application of management accounting depends on strong leadership commitment, competent human resources, and the adoption of good governance principles. Therefore, management accounting serves not only as an administrative necessity but also as a foundational tool for delivering high-quality and trustworthy public services.

This study evaluates the relationship between the Automatic Dependent Surveillance - Broadcast (ADS-B) system and safety in air traffic management at the Semarang Branch of Perum LPPNPI. The need for enhanced efficiency and operational safety in air travel has increased, particularly following the rise in aircraft movements post-COVID-19. ADS-B, a satellite-based monitoring system, provides real-time data on aircraft position, speed, and altitude to air traffic controllers, facilitating quick and accurate decision-making. Employing a quantitative associative approach, the study uses saturated sampling, including all 26 active Air Traffic Controller personnel at the Semarang Branch. Data were gathered through a Likert scale questionnaire measuring respondents' perceptions of the variables. Analysis using SPSS revealed a significance value of 0.000, indicating a statistically significant relationship between ADS-B usage and flight safety. The correlation coefficient of 0.780 demonstrates a strong positive relationship, while the determination coefficient of 0.608 indicates that 60.8% of variations in flight safety can be attributed to the ADS-B system. Additionally, the t-test results confirm that the calculated t value exceeds the t table, reinforcing the conclusion of a significant and consistent relationship between the variables.

This study is to develop a web-based inventory management information system for grocery merchants in order to speed up the stock recording process. The system is built according to the waterfall style of system development, using PHP and MySQL. Data collection techniques include observation, interviews, and literature research. As a result, store managers can improve operating efficiency and reduce errors in manual stocktaking by using a system that allows real-time product stock input, updating, and monitoring. This study provides a practical digital solution to support the digitization of small businesses in Indonesia.

The research method employed is a descriptive qualitative approach, with data collection techniques including observation, in-depth interviews, and documentation. Informants for this study consisted of the school principal, teachers, students, and community members. The research findings indicate the implementation of quality assurance management. First, a plan is developed related to the vision and mission as the goals to be achieved. Second, organization by the Madrasah Quality Assurance Team focuses on quality. Third, implementation involves a series of activities, such as teacher training and the implementation of a structured evaluation system. Fourth, for control, the principal and the QAT (Quality Assurance Team) actively motivate all school elements. Fifth, the guidance phase involves continuous control through periodic monitoring and evaluation of the quality assurance program's implementation, supported by the PDCA (Plan-Do-Check-Act) theory. Efforts to enhance trust include an emotional approach, offering programs that align with community needs, and consistently providing updates on student progress through social media