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This community service activity was conducted at Grind Now Coffee Bar, an MSME in Batam City’s food and beverage sector, to address challenges in managing raw material inventory, which often led to inaccurate stock records, shortages, and overstocking, affecting daily operations and efficiency. The program aimed to improve inventory management by applying the Economic Order Quantity (EOQ) and Reorder Point (ROP) models, providing a systematic and measurable approach to procurement. Activities included detailed observation of operational practices, interviews with staff to understand current challenges, collection of data on raw material usage and purchasing patterns, and the implementation of a website-based inventory control system to streamline record-keeping and monitoring. The results showed that EOQ and ROP models helped determine optimal order quantities and appropriate reorder timing, while the inventory system improved organization, reduced errors, and enabled real-time stock monitoring. Overall, this intervention enhanced decision-making, promoted operational efficiency, and supported the sustainability and competitiveness of Grind Now Coffee Bar.

Traditional food is a national asset. It not only serves as a source of energy for the community, but also serves as a form of food security, an economic driver, a source of healthy food, and a culture steeped in noble values. The widespread consumption of unhealthy foods by students, especially elementary school students, is one of the reasons for this outreach activity. The health issues surrounding junk food must be addressed by offering healthy alternatives, such as traditional foods. Traditional food is not only related to food, but can also be linked to ethnomathematics, where culture in the form of food is studied from a mathematical perspective. Elementary school students not only consume traditional foods but also interpret these foods in mathematical contexts, such as geometry and numbers. In this way, students will be able to visualize mathematical elements not only when reading math textbooks but also when consuming traditional foods that are part of their daily environment. Despite their traditional nature, students actually enjoy some traditional foods. This is a frequent conflict between the current generation and traditional culture. They better understand how to prepare traditional foods, appreciate the richness of local culture, and develop a love for their culture and homeland.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

This study analyzes the implementation of Islamic inheritance law (mawaris) in contemporary Muslim society as a means to realize justice and blessing (barakah) in the distribution of inherited wealth. The research is motivated by the growing number of inheritance disputes caused by limited understanding of faraid principles, the persistence of customary inheritance practices, and the coexistence of national legal systems that often diverge from Islamic inheritance regulations. These conditions frequently lead to unequal distribution and family conflicts. The study aims to examine the relevance of mawaris in modern contexts and to explore how its application, when aligned with the objectives of Islamic law (maqasid al-shariah), can address current social challenges. Employing a qualitative method with a normative library research approach, the study draws on primary sources such as the Qur’an, Hadith, and classical fiqh texts, as well as secondary sources including contemporary books and scholarly journal articles. Data were analyzed through content analysis to identify key concepts and arguments regarding the contemporary application of mawaris. The findings show that proper implementation of Islamic inheritance law fosters justice, minimizes family disputes, strengthens kinship ties, and safeguards the blessing of wealth. Nevertheless, insufficient public literacy on Islamic inheritance law and the dominance of non-sharia considerations remain significant barriers. Therefore, the study underscores the need for enhanced public education, greater involvement of religious scholars in inheritance mediation, and contextual integration of Islamic legal principles to ensure fair and beneficial inheritance distribution in modern Muslim families.

This research investigates the effect of fundamental factors, namely the current ratio, debt to equity ratio, and return on equity on stock returns of mining firms listed on the Indonesia Stock Exchange (IDX) during 2021–2023. The research highlights the utility of understanding a firm’s financial performance in guiding investment selection within the capital market. Although the mining industry contributes significantly to Indonesia’s economy, stock movements in this sector are often subject to uncertainty due to market fluctuations and commodity price volatility. This research utilizes secondary data from annual financial statements and stock price records of 51 IDX-listed mining companies over the study period. Panel data regression, combined with descriptive and quantitative statistical techniques, was employed using E-Views 12 software. The findings reveal that stock returns are significantly influenced by the current ratio, debt to equity ratio, and return on equity. These results provide useful insights for investors, financial analysts, and corporate management by emphasizing the function of fundamental indicators in assessing stock performance, particularly within the mining sector.

In the current era of digital transformation, organizations are increasingly turning to Artificial Intelligence (AI) to enhance the precision and agility of managerial decisions. This study investigates how AI adoption within management accounting systems influences decision-making efficiency and managerial performance. Using survey data collected from managers and accountants in medium-to-large firms across Central Java, the research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the hypothesized relationships. The results reveal that AI adoption significantly improves decision-making efficiency, which in turn enhances managerial performance. Furthermore, leadership support strengthens the relationship between AI adoption and decision-making efficiency, indicating that human and organizational factors remain critical for realizing technological benefits. The findings contribute to management accounting literature by elucidating the mechanism through which AI technologies create managerial value specifically, by accelerating analytical processes and improving the quality of managerial judgments. Practically, the study suggests that firms should focus on leadership involvement, data governance, and employee training to ensure that AI systems complement, rather than replace, human judgment. Overall, this study highlights that successful AI adoption in management accounting is not merely a technical transition but a strategic and cultural evolution toward evidence-based decision-making.

This study analyzes the forms of risk and risk management strategies in melon farming in Brebes as an impact of climate change. A descriptive qualitative approach was applied using a case study through in-depth interviews with a farmer who has more than ten years of experience, supported by secondary data from BPS, BAPPENAS, and related literature. The findings reveal four categories of major risks: market, financial, operational, and socio-environmental. High-level risks include climate variability, yield decline, and pest attacks. Medium-level risks involve production costs, water management, and price fluctuations, while low-level risks consist of limited weather information and agricultural extension services. Current strategies are still basic, including fertilization, pesticide application, and water channel arrangement. Strengthening adaptation is needed through irrigation technology, climate-resilient varieties, marketing diversification, and improved access to information and institutional support.

This study aims to determine and analyze service waiting times, identify the root causes of long queues, and develop a strategy to improve service performance at the 5361137-gas station (SPBU) at the Surabaya-Gresik Toll Rest Area. The research method used is a mixed-methods approach with an exploratory sequential design. This study combines quantitative analysis using Queuing Theory to measure system performance (arrival rates and service times) and descriptive qualitative analysis using a Fishbone Diagram. Data were collected through direct observation, interviews, and g-form techniques. The results indicate that the current queuing system performance is in a critical or severe condition, indicated by a server utilization rate of 0.94 to 1.02 during peak hours. The average time spent by vehicles in the system is 14.3 minutes, of which 9.6 minutes (67%) is spent waiting in the queue. Fishbone diagram analysis revealed that the root cause of the main problem lies in the complex interaction of factors: Machine factors (EDC signal failure and pump repair downtime), Human and Method factors (implementation of static shifts and reactive maintenance), and Environmental factors (narrow layouts that hinder large vehicle maneuvers). As a solution, this study formulated a hybrid improvement strategy that includes short-term business process engineering (the use of Floating Staff and lane segregation) and long-term investment in additional pumps to change the queuing model from Single Channel to Dual Channel. This strategy is expected to reduce the utility level to a safe zone below 0.80 with a target waiting time of 3–5 minutes.

This paper reviews the role of Artificial Intelligence (AI) in Islamic education within secondary schools, emphasizing both its practical uses and the ethical challenges it presents. The review looks into the current trends, tools, and the impact of AI on the learning experience, as well as its ethical implications from an Islamic perspective. The study follows a systematic literature review (SLR) approach based on the PRISMA guidelines and includes research from 2022 to 2025, sourced from platforms like Google Scholar. After a thorough selection process, 15 articles were included in the review, offering valuable insights into the technological and ethical aspects of AI in Islamic secondary education. The use of AI has notably enhanced learning outcomes in Islamic education by allowing personalized learning, boosting student engagement, and streamlining feedback mechanisms. Tools like intelligent tutoring systems and educational chatbots have been widely adopted. However, challenges around data privacy, algorithmic bias, and technology access persist. Additionally, incorporating Islamic ethical values into AI-driven educational platforms presents both opportunities and challenges. Addressing these ethical implications is vital, requiring frameworks that align with Islamic principles such as maṣlaḥa (public welfare), justice, and human dignity. Education policies and teacher training programs should concentrate on promoting the responsible use of AI, ensuring it improves educational experiences while preserving ethical and cultural integrity.

The integration of artificial intelligence (AI) in forensic investigation has significantly transformed the analysis and authentication of digital evidence. This paper explores the role of AI technologies, specifically machine learning and deep learning algorithms, in examining digital evidence from various sources, including computers, mobile devices, and network systems. We provide an in-depth analysis of current AI-based forensic tools, their efficiency in evidence authentication, and the challenges they face regarding legal admissibility. Our findings indicate that AI-powered forensic systems can detect digital evidence tampering with 94.7% accuracy, drastically reducing analysis time from weeks to hours. However, challenges remain, particularly in areas such as algorithmic transparency, bias prevention, and ensuring the integrity of the chain of custody. This research offers a framework for incorporating AI in forensic laboratories, while also addressing crucial legal and ethical concerns to ensure the admissibility of AI-analyzed evidence in court. These considerations are essential for the widespread acceptance and use of AI in forensic investigations.

The determination of the beginning of the lunar month is an important issue in religious practice and the establishment of the Hijri calendar in Indonesia. The diversity of imkan rukyat criteria used across countries necessitates an evaluation of international standards, including the 2016 Turkish Criteria, which are considered more progressive with parameters of a minimum crescent altitude of 5° and an elongation of 8°. This article examines the relevance of the 2016 Turkish Criteria within the astronomical and jurisprudential context of Indonesia, as well as its implications for the process of determining the beginning of the lunar month by the government and Islamic organizations. Through literature review, comparative astronomical analysis, and examination of hisab–rukyat practices in recent years, this study finds that the 2016 Turkish Criteria exhibit strong astronomical consistency and can enhance calendar predictability. However, its application in Indonesia may lead to discrepancies with the government’s criteria, which currently require a crescent altitude of 3° and an elongation of 6.4°. These implications include potential differences in month beginnings, the need for harmonizing criteria, and the importance of dialogue between national and international astronomical authorities. This study recommends strengthening astronomical and jurisprudential assessments prior to adopting new criteria and encourages the integration of global data to improve the accuracy of the Hijri calendar in Indonesia.

Flooding is one of the most recurrent natural disasters in Central Java Province, particularly during the rainy season. Diverse geographical characteristics, high rainfall intensity, and rapid urban development contribute to the region’s high vulnerability to flood hazards. According to the Central Java Statistics Agency, a total of 414 flood events and 407,784 affected victims were recorded between 2019 and 2021. This study aims to develop a web-based Geographic Information System (GIS) capable of mapping the spatial distribution and impact levels of floods across Central Java. The methodology includes collecting flood event data from the Central Java Statistics Agency, processing spatial data such as administrative boundary shapefiles, performing attribute integration between spatial and non-spatial datasets, and creating thematic maps using QGIS. The visualization outputs were exported into an interactive web format using the qgis2web plugin and subsequently integrated into a website developed with HTML, CSS, and JavaScript. The results show that the GIS system successfully visualizes flood-prone areas, identifies regions with high flood intensity, and enables users to explore detailed information through interactive digital maps. Additional website features—such as historical flood data, statistical summaries, and descriptive impact indicators—enhance the system's usefulness for disaster analysis. This study demonstrates the crucial role of GIS in supporting disaster mitigation, spatial planning, and policy evaluation related to flood management. Future research is recommended to incorporate more recent datasets and additional non-spatial variables such as rainfall intensity and floodwater depth to improve the system’s analytical accuracy and comprehensiveness.

This study aims to design and develop an electrical installation panel by applying engineering safety principles in the water spray booth of a vehicle body painting system. Field observations indicate that electrical panels in painting rooms often do not meet safety standards, which can lead to short circuits and potential fire hazards. The research employed a Research and Development (R&D) method using a simplified Borg and Gall model consisting of nine stages, starting from problem identification to effectiveness testing. Expert validation results obtained a score of 87.5% (highly valid), practicality testing yielded 90% (very practical), and effectiveness tests showed an average current of 4.1 A, with both the MCB and emergency stop functioning optimally. The developed panel product is declared feasible to be used as a practical learning media for automotive electrical systems. Based on the test results, the panel product was declared suitable for use and can be used as a learning medium in automotive electrical practice, helping to increase understanding of the application of safety in electrical installations in the automotive industry.  

Pepper is currently not only used to meet daily needs but also as an export commodity. Indonesian pepper exports generate foreign exchange for the country. Currently, international competition for pepper exports is increasingly fierce. An evaluation of the level of market competition and the structure of the pepper market at the international level is necessary. The methods used to analyze the level of competition concentration and market structure are the Concentration Ratio of Biggest Four (CR4) and the Herfindahl-Hirschman Index (HHI). The types of pepper discussed in this study are white pepper with HS code 090411 and black pepper with HS code 090412. The results obtained indicate that both black and white pepper tend to be in an oligopoly market structure with a relatively high level of competition. Such market conditions are a distinct advantage for Indonesia, as there are not too many competitors while buyers or enthusiasts are quite high. A striking difference occurs in the international black pepper trade. In the black pepper trade, Indonesia is not classified as a country with the largest market share.

Intensive exploitation of fish for caviar production currently threatens the extinction of sturgeon, one of the ancient fish species. Sturgeon egg harvesting is often carried out in inhumane ways, such as dissecting and killing parent fish, causing the natural sturgeon population to decline. The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) regulates the international trade of sturgeon and caviar, but weak law enforcement, high market demand, and widespread illegal trade all exacerbate the conservation status of this species. Conversely, caviar aquaculture, often considered an alternative, raises new bioethical issues, including long-term stress on fish, disease spread, decline in animal health, and the risk of hybridization that could threaten the genetic integrity of sturgeon populations. From a bioethical and environmental ethics perspective, it is difficult to justify the consumption of caviar as a luxury commodity at the expense of ecosystem sustainability and animal welfare. Therefore, sturgeon conservation requires a comprehensive approach that includes reducing consumer demand, improving legislation and enforcement, and preserving and restoring sturgeon's natural habitats.

The emergence of ChatGPT and other large language models has introduced unprecedented opportunities and challenges in educational settings. This study examines the dual nature of ChatGPT's integration into classroom environments, analyzing both its potential as an educational tool and the ethical concerns it raises regarding academic integrity. Through a mixed-methods approach combining surveys, interviews, and content analysis, this research investigates how educators and students perceive and utilize ChatGPT, the implications for learning outcomes, and the effectiveness of current academic integrity policies. Results indicate that while ChatGPT offers significant pedagogical benefits including personalized learning support and enhanced accessibility, it simultaneously poses risks to traditional assessment methods and raises questions about authorship and original thought. The study proposes a framework for responsible AI integration in education that balances innovation with academic integrity, emphasizing the need for updated policies, enhanced digital literacy, and redesigned assessment strategies. These findings contribute to the ongoing discourse on AI in education and provide practical recommendations for educators, administrators, and policymakers navigating this transformative technology.

This study examines the implementation of RoRo ship services in Indonesia, highlighting the implementation of RoRo ships and the current national logistics framework potential strategies, particularly in the 3T region. This research employs a qualitative descriptive methodology that includes a literature review. It utilizes secondary data from previous studies, comprising books and original scientific reports published in articles or journals. The findings indicated 1) The use of RoRo ships has gone through progressive developments, like the government's initiative on “Sea Toll” designed to support the logistics sector, particularly in 3T regions. 2) Enhancing the logistics framework through the integration of National Logistic EcosIstem (NLE) alongside the Internet of Things (IoT) to increase logistics efficiency that is rapid, effective, and clear. Nevertheless, these initiatives faces challenges. Consequently. The proposed strategies focus on improving growth center development through logistics integration (shipping, port management, and intermodal) and implementing digitalization in logistics document processing.

Elderly people are individuals aged 60 and over who have equal rights in community life. The emotional state of the elderly is a psychological state that encompasses the ability to think, feel, and act, as manifested through behavior. To stabilize the emotions of the elderly, cadres and their families must have an adequate level of emotional intelligence. One non-pharmacological approach currently being studied is the Spiritual Emotional Freedom Technique (SEFT), an emotional healing method that combines spiritual elements, positive affirmations, and stimulation of the body's meridian points. SEFT is believed to reduce psychological stress that contributes to high blood pressure. This therapy is easy to learn, can be performed independently, and requires no special equipment, making it highly suitable for use in elderly communities with limited access to advanced medical services. At this event, counselors provided support in delivering material on Motivation and Prevention of Psychological Disorders in the Elderly using the SEFT. The purpose of this material is to provide motivation, reduce, and prevent psychological impacts. Participants benefited from the material, knowledge, and experience sharing, as well as solutions, resulting in a better understanding of motivation, reduction, and prevention of psychological impacts. This community service program was conducted with approximately 33 participants in the "Teratai" elderly group. It is hoped that this community service program will be beneficial and provide considerations for solutions and decisions, adding information and insight related to motivation, reduction, and prevention of psychological impacts.

Medical emergency services demand swift and precise action; however, medical personnel are often hindered by the risk of criminalization resulting from unintended outcomes. Although Law Number 17 of 2023 concerning Health mandates the provision of assistance, the regulation has not yet provided explicit criminal protection for good-faith rescuers, thereby triggering the practice of defensive medicine. This study aims to examine the implementation of the Good Samaritan Law (GSL) concept as an alternative legal protection for health workers. The research methods employed are juridical-normative and juridical-empirical, utilizing statutory, comparative, and case approaches. The findings indicate that current regulations, including Article 531 of the Criminal Code (KUHP) and Law No. 17/2023, have limitations as they emphasize the obligation to assist rather than the protection of the rescuer. In comparison, the international GSL concept offers a standard of "limited immunity," which explicitly protects rescuers from civil and criminal liability, provided the actions are performed without gross negligence. The impact of implementing GSL in Indonesia is projected to provide stronger legal certainty than existing regulations, reduce the psychological burden on medical personnel in emergency situations, and encourage social solidarity without the fear of unnecessary lawsuits. The study concludes that the adoption of GSL is an urgent legal reconstruction to ensure the professional protection of health workers in Indonesia.

This study uses a qualitative method of a descriptive approach with an interpretive paradigm to gain an in-depth understanding of the process of planning, implementing, and evaluating broadcast programs. This research was carried out at the Communication and Information Office of Bogor Regency, Jalan Tegar Beriman Number 1, Pakansari, Cibinong District, Bogor Regency, West Java 16914. The data collection techniques used are direct observation of the broadcast process, in-depth interviews with broadcasters and program managers, and documentation to support the validity of research data. The results of this study show that broadcasting strategies are implemented through content planning that suits the needs of listeners, the implementation of interactive broadcasts involving listeners and routine evaluation to maintain the quality of the information that has been delivered. In addition, the use of digital media as a streaming platform and interaction through social media also supports a wider reach to listeners. The conclusion of the broadcasting strategy implemented by Radio Teman 95.3 FM is considered effective in maintaining listener loyalty and attracting new audiences, so that it can be an example for other local radio stations in facing the current digital media competition.technological optimization, audience engagement, and adaptation to the development of new media.