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Diabetes mellitus is a chronic disease that requires long-term pharmacological therapy, increasing the risk of Drug Related Problems (DRPs). DRPs can affect the success of therapy, increase the risk of complications, and reduce the patient's quality of life. This article aims to identify the use of antidiabetic drugs, the characteristics of DRPs, and their clinical implications. The method used was a literature review of articles from 2016-2026 that are relevant to the analysis of DRPs in diabetes mellitus patients. The results of the study indicate that metformin is the most widely used antidiabetic drug, both as a single therapy and in combination. The dominant types of DRPs include drug interactions, inappropriate drug selection, inappropriate dosages, omissions from therapy, and use of drugs without indications. These DRPs can cause hypoglycemia, failure to achieve glycemic control targets, an increased risk of complications, and increased duration and cost of treatment. Based on the results of the study, it is concluded that DRPs remain a challenge in the management of diabetes mellitus therapy, requiring more optimal monitoring and an active role of pharmacists through medication review to improve the safety, effectiveness, and quality of treatment.

This study aims to analyze the implementation of efficiency, effectiveness, and consistency in the Standard Operating Procedure for goods procurement in the purchasing department of The Oberoi Beach Resort, Bali. This research employed a descriptive qualitative approach, with data collected through semi-structured interviews, observation, and documentation. The informants included parties directly involved in procurement activities, namely the Purchasing Manager, Purchasing Supervisor, Purchasing Staff, Receiving Staff, and user departments. Data were analyzed through data reduction, data display, and conclusion drawing and verification. The findings show that the goods procurement SOP has been implemented in a structured manner through Purchase Requisition submission, document approval, Purchase Order issuance, supplier ordering, and goods inspection by the receiving department. The SOP is effective in supporting hotel operational needs and relatively consistent because control stages are maintained even under urgent requests. However, efficiency has not been fully optimized because administrative and approval processes still rely on a manual paper-based system. Other barriers include inventory data input errors, supplier stock limitations, customs constraints, and weather-related distribution disruptions. This study recommends the implementation of e-procurement, stronger interdepartmental coordination, improved inventory data accuracy, and supplier diversification.

The implementation of Income Tax Article 22 on import activities plays a strategic role in securing state revenue and controlling international trade flows. However, corporate taxpayers frequently encounter substantial barriers regarding regulatory compliance and technical administrative procedures. This study aims to analyze the compliance level of corporate taxpayers concerning the collection and reporting of Income Tax Article 22 on import activities, while identifying the primary obstacles faced during the process. The research employs a qualitative descriptive method with a case study approach conducted at the Tax Allowance Office. Primary data were gathered through semi-structured interviews with corporate taxpayers and tax authorities, supplemented by secondary data from tax compliance reports and related documentation. The findings indicate that while formal compliance regarding timely reporting has significantly improved due to digital administrative transformations like the e-Bupot system, substantial challenges remain in material compliance. Corporate taxpayers routinely face difficulties in classifying import tariff codes accurately and interpreting the frequent updates to tax incentives. This study implies that the tax authority needs to intensify specialized socialization programs and optimize the integration of data systems between the Directorate General of Taxes and the Directorate General of Customs and Excise. These strategic improvements are crucial to minimizing administrative discrepancies and enhancing overall tax compliance.

This qualitative study aims to explore the effectiveness of reward-and-punishment-based Islamic Religious Education in strengthening students' learning motivation at SMA Negeri 1 Bukateja using Travis Hirschi's social control theory framework. This research was conducted through a case study approach in one of the public high schools in Purbalingga Regency. Data were collected through interviews, participant observation, and documentation studies. The results of the study indicate that the implementation of rewards and punishments functions as a social control mechanism that is able to activate four elements of social bonds: attachment, commitment, involvement, and trust. The reward system in the form of praise, certificates, and gifts has been proven to strengthen the emotional bond between students and teachers, thereby increasing active participation and enthusiasm for learning. Meanwhile, educational punishments, such as reprimands, additional assignments, and community service, are able to build student commitment to rules and reduce indiscipline behavior.This study contributes to the development of Islamic education theory through a social control perspective and serves as a practical reference for Islamic Religious Education teachers in designing effective, fair, and sustainable learning systems.

This study aims to analyze the effect of capital structure, asset growth, and firm size on firm value in plastic and packaging sub-sector companies listed on the Indonesia Stock Exchange during the 2020–2024 period. Firm value is proxied by Price to Book Value (PBV), capital structure is measured using the Debt to Equity Ratio (DER), asset growth is measured by the asset growth ratio, and firm size is measured using the natural logarithm of total assets. This research employed an explanatory quantitative approach using secondary data obtained from financial statements, annual reports, and stock price data. The sample consisted of 11 companies observed over five years, resulting in 55 panel data observations. Data were analyzed using panel data regression through the Common Effect Model, Fixed Effect Model, and Random Effect Model, with model selection based on the Chow, Hausman, and Lagrange Multiplier tests. The results indicate that capital structure, asset growth, and firm size have no significant effect on firm value, either partially or simultaneously. These findings suggest that firm value in the plastic and packaging sub-sector is not sufficiently explained by financing structure, asset expansion, or company size. Investors are more likely to consider other factors, such as profitability, operational efficiency, cash flow, sales growth, raw material risk, and sustainability prospects. Therefore, companies should improve financial performance, asset efficiency, cost control, and sustainable innovation to enhance firm value.

Lake Rawa Pening is one of Indonesia’s priority lakes facing serious ecological pressure due to the rapid proliferation of water hyacinth. This study aims to classify and map the distribution of water hyacinth in Rawa Pening Lake during the 2021–2025 period and to analyze the seasonal distribution patterns of water hyacinth. Sentinel-2 imagery processed on the Google Earth Engine platform was classified using the Random Forest algorithm combined with hybrid sampling and spectral indices (NDVI, NDWI, MNDWI, and SRI). Classification accuracy assessment showed high performance with an Overall Accuracy of 97.45% and a Kappa coefficient of 0.949. The results indicate significant spatial-temporal fluctuations, with the highest coverage recorded in March–April 2021 (855.75 ha) and the lowest in May–June 2022 (108.44 ha). Seasonal-Trend Decomposition using Loess (STL) revealed consistent seasonal patterns, with peak expansion occurring during the rainy season, particularly in January–February. Although initial implementation of lake management policies reduced coverage, subsequent increases suggest that control measures remain insufficiently sustainable. This study demonstrates the effectiveness of cloud-based satellite monitoring for evaluating lake management policies and supporting evidence-based environmental management strategies.

Heat stress is a major constraint in broiler production systems located in humid tropical climates, where high ambient temperature and relative humidity impair growth performance, feed efficiency, and animal welfare. This systematic review synthesizes peer-reviewed studies published between January 2015 and December 2025 evaluating environmental housing designs and cooling strategies for mitigating heat stress in broiler chickens. This systematic review followed the PRISMA 2020 guidelines and synthesized peer-reviewed studies retrieved from Scopus, Web of Science, and ScienceDirect, published between January 2015 and December 2025. From 500 records initially identified, 26 studies fulfilled the predefined eligibility criteria and were included in the qualitative synthesis. The findings demonstrate that evaporative cooling systems, tunnel ventilation, and automated climate control technologies consistently reduced indoor temperature (2–6°C) and improved body weight gain, feed conversion ratio (FCR), and mortality rates under hot-humid conditions. However, cooling efficiency was strongly influenced by ambient humidity, necessitating integrated and adaptive environmental control approaches. Smart sensor-based systems further enhanced microclimate stability and thermal uniformity within broiler houses. Beyond performance improvements, optimized environmental management reduced physiological stress indicators, including heterophil-to-lymphocyte ratios and corticosterone levels. Overall, integrated, humidity-adaptive, and energy-efficient cooling strategies are essential to sustain productivity, welfare, and climate resilience in tropical broiler production systems.

Poultry agribusiness is a key driver of food security and rural economic development in developing countries. However, the sector remains vulnerable to infectious diseases such as avian influenza and Newcastle disease, which can disrupt production systems and supply chain continuity. Although previous studies have examined poultry disease control, biosecurity, and supply chain disruption, evidence on how risk and crisis communication supports outbreak management and resilience in developing-country poultry agribusiness remains fragmented. This study applied a systematic literature review (SLR) approach under PRISMA guidelines to synthesize risk and crisis communication strategies in poultry disease management and their contribution to supply chain resilience. Only seven relevant studies published between 2020 and 2025 met the inclusion criteria and were analyzed using the PICO framework. Quality assessment using the Mixed Methods Appraisal Tool (MMAT), combined with systematic data extraction in Microsoft Excel 2021, was conducted to improve methodological transparency and consistency. The novelty of this review lies in integrating communication strategies, enabling and constraining factors, digital tools, One Health perspectives, and public–private collaboration within a single analytical synthesis. The findings indicate that participatory, transparent, and coordinated communication can support disease prevention and crisis preparedness, particularly when strengthened by stakeholder trust, policy support, training, and accessible information channels. However, limited digital literacy, inadequate infrastructure, and cultural barriers may reduce communication effectiveness. Overall, this review highlights the need for inclusive communication systems and collaborative governance to strengthen poultry supply chain resilience in developing countries, while recognizing that the small evidence base limits broad generalization.

Background: Low birth weight (LBW) remains a major public health concern worldwide due to its significant contribution to neonatal morbidity and mortality, as well as its long-term adverse health consequences. Pregnancy intention has been identified as a potential determinant of adverse birth outcomes; however, evidence regarding its association with LBW remains inconsistent. This study aimed to examine the association between pregnancy intention and low birth weight in Indonesia using data from the 2012 Indonesian Demographic and Health Survey (IDHS). A cross-sectional study was conducted using secondary data from the 2012 IDHS. The study included 8,922 married women aged 15–49 years who had a singleton live birth within five years preceding the survey. Pregnancy intention was categorized as intended, mistimed, and unwanted. Multivariable logistic regression analysis was performed to assess the association between pregnancy intention and LBW after controlling for potential confounding variables. The prevalence of LBW was 6.2%. After adjustment for maternal age and antenatal care (ANC) visits, no significant association was found between mistimed pregnancy and LBW (AOR = 1.055; 95% CI: 0.765–1.454). An interaction effect was identified between unwanted pregnancy and pregnancy complications. Women with unwanted pregnancies accompanied by pregnancy complications had a higher risk of delivering LBW infants compared with women whose pregnancies were intended and without complications. Nevertheless, pregnancy intention was not significantly associated with LBW overall after adjustment for confounding factors. Maternal age outside the optimal reproductive age range (<20 years or >35 years) and inadequate ANC utilization were significantly associated with an increased risk of LBW. Pregnancy intention was not independently associated with low birth weight among Indonesian women after controlling for maternal and healthcare-related factors. Maternal age and antenatal care utilization were more consistent determinants of LBW. Strengthening maternal health services, particularly adequate antenatal care and early detection of pregnancy complications, may contribute to reducing the burden of low birth weight in Indonesia.

Image Quality Assessment has become an important research area in computer vision due to the increasing use of digital imaging in medical, industrial, and remote sensing applications. This study conducted a Systematic Literature Review (SLR) using articles retrieved exclusively from the Scopus database. A total of fifteen Scopus-indexed articles were selected through the PRISMA process consisting of identification, screening, eligibility, and inclusion stages. The findings indicated that convolutional neural networks, transformer architectures, and no-reference approaches dominated recent studies because of their ability to capture complex visual features and improve evaluation accuracy. The application domain strongly influenced method selection, particularly in medical imaging, industrial quality control, and remote sensing. Deep learning methods achieved high performance but required large datasets and high computational resources. Overall, recent research trends shifted from traditional image enhancement toward artificial intelligence-based quality evaluation.

The rapid growth of Solar Power Plant (PLTS) installations in Indonesia faces efficiency challenges due to the continuously changing position of the sun. Fixed panel systems cannot absorb solar radiation optimally throughout the day. This study aims to evaluate and compare the efficiency of various solar tracking system methods developed over the last five years using a simple literature review approach. The research method was conducted by collecting, screening, and synthesizing secondary data from five reputable scientific journals using a synthesis matrix. The review results indicate that single-axis tracking systems increase power efficiency by 15% to 24.5%. Meanwhile, dual-axis systems achieve higher efficiency, ranging from 30% to 35%, by tracking both horizontal and vertical solar movements. In terms of control systems, astronomical algorithms are found to be more reliable in cloudy weather conditions than pure light sensors. However, the internal power consumption of the actuator motors remains a critical factor that can reduce the system's net energy gain. The implication of this study emphasizes the importance of shifting future research focus toward energy-saving algorithm optimization to maximize net power yield in dynamic solar panel implementations.

Early Marriage in Pagar Alam City is currently still quite high, the Pagar Alam Religious Court only relies on a recap of the number of cases per year to draw conclusions about the early marriage data. This method has limitations in classifying early marriage factors, so the Religious Court has difficulty in monitoring and controlling the occurrence of Early Marriage in Pagar Alam City. The purpose of this research thesis is to produce a classification system for Early Marriage factors using the K-Nearest Neighbor Algorithm to find out what factors influence the occurrence of Early Marriage, the method used in this study is the Cross Industry Standard Process for Data Mining (CRISP-DM) which has 6 stages, namely: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The testing stage in this study uses Confusion Matrix and BlackBox Testing. The final results of this study indicate that the system can classify Early Marriage factors. The classification model built achieved an Accuracy of 94.12% and a Precise value of 85.71% and a Recall value of 100.00%, while testing using Black Box testing in the form of alpha obtained a feasibility value of 83.2%, so this system is very suitable for use.  

concern for pet owners. Consequently, cat owners seek equipment that can support and simplify their daily pet care activities. However, the busy schedules of many cat owners often make it difficult for them to provide consistent care, raising concerns about the neglect of their pets. To address this issue, this study developed an automatic cat feeding system for a cat enclosure using an experimental research method. The proposed system utilizes a load cell sensor, a Real-Time Clock (RTC), a servo motor, and an ATmega16 microcontroller. The load cell sensor is employed to determine the appropriate food portion based on the cat's nutritional requirements, while the RTC controls the feeding schedule by dispensing food twice a day at predetermined times. The experimental results demonstrate that the system was successfully implemented, with the load cell measurement exhibiting an error rate of 10.71% relative to the predefined set point. Furthermore, the servo motor effectively controlled the valve mechanism, achieving a maximum opening angle of 85 degrees. Overall, the developed system performed reliably and met the expected operational objectives..

Digital technology advancements have greatly changed how small businesses manage their finances. This change is not only about recording transactions, but it also affects financial control, report preparation, and business decision making. Accounting Information System (SIA) came about as a solution to help small and medium businesses easily, organize, and accurately record their finances, as well as provide reliable financial information. This study aims to explain the role of the Accounting Information System in making it easier to manage the finances of small and medium businesses in the digital age, the benefits gained from using it, and the challenges faced during its implementation. The method used in this research is a literature review, which involves examining books, journals, and other related scientific publications, followed by analysis using a descriptive qualitative approach. Research findings show that using a digital-based Accounting Information System can improve business efficiency, speed up financial reporting, increase transparency, and make it easier for small and medium-sized businesses to get funding access. However, the implementation of the Accounting Information System still faces challenges such as a lack of technological understanding, limited infrastructure, and high implementation costs. Therefore, collaboration and support from various parties are needed to ensure the accounting information system is implemented effectively and sustainably in small and medium businesses.

Acute Respiratory Infection (ARI) remains a major public health problem in Indonesia. Based on the 2025 National Health Reporting System survey, ARI ranked first among diseases with the highest number of cases, reaching more than 14.5 million cases. This study aimed to determine and analyze the relationship between environmental sanitation and nutritional status with the incidence of ARI among children under five following flood disasters in the working area of Panteraja Community Health Center, Pidie Jaya Regency. The study employed a quantitative method with an analytical observational design using a case-control approach. The dependent variable was the incidence of ARI among under-five children, while the independent variables were environmental sanitation and nutritional status. The sample consisted of 122 children under five, including 61 children with ARI and 61 children without ARI. The results of the chi-square test showed a significant relationship between environmental sanitation and ARI incidence (p = 0.000; OR = 0.042; 95% CI = 0.014–0.133), as well as between nutritional status and ARI incidence (p = 0.000; OR = 0.011; 95% CI = 0.001–0.083). These findings indicate that poor environmental sanitation and inadequate nutritional status contribute to the occurrence of ARI among children under five after flooding. Therefore, promotive and preventive efforts, along with regular monitoring of children's nutritional status, are essential to reduce the risk of ARI.

Stroke remains one of the leading causes of mortality and disability worldwide, including in Indonesia. The increasing prevalence of stroke and Years Lived with Disability (YLD) reflects its growing health burden. This study aimed to analyze trends in stroke prevalence and YLD in Indonesia during 2021–2023 using data from the Global Burden of Disease (GBD). A quantitative descriptive design with an ecological and time-trend approach was employed. Secondary data were obtained from the GBD Results Tool and analyzed using R version 4.4.1. The analysis focused on major geographical regions across Indonesia. The results showed a gradual increase in both stroke prevalence and YLD during the study period. Java recorded the highest prevalence and YLD, while Maluku and Papua showed lower prevalence but greater variation in YLD. These trends were associated with urbanization, unhealthy lifestyles, hypertension, diabetes, and unequal access to healthcare and rehabilitation services. Pearson correlation analysis demonstrated a very strong association between stroke prevalence and YLD (r > 0.99) across all years. The findings highlight increasing stroke burden and regional disparities, emphasizing the need for equitable healthcare access, risk factor control, and strengthened post-stroke rehabilitation programs.

This study aims to analyze the influence of work motivation and supervision on employee performance through job satisfaction at the Population Control and Family Planning Office (DPPKB) of East Kutai Regency. A quantitative approach was employed using census sampling technique involving 84 employees. Data were analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS) with SmartPLS software. The results reveal that: (1) work motivation positively and significantly affects job satisfaction (β = 0.263, p = 0.039); (2) supervision has a stronger positive effect on job satisfaction (β = 0.409, p = 0.000); (3) work motivation does not directly affect employee performance (β = 0.136, p = 0.248); (4) supervision does not directly affect employee performance (β = 0.140, p = 0.186); (5) job satisfaction is the strongest predictor of employee performance (β = 0.565, p = 0.000); (6) job satisfaction does not significantly mediate the work motivation–performance relationship (β = 0.149, p = 0.056); and (7) job satisfaction fully mediates the supervision–performance relationship (β = 0.231, p = 0.001). These findings suggest that improving public-sector employee performance requires a humanistic supervisory approach centered on employee psychological well-being.

The emergence of Internet of Things (IoT) technology has opened up considerable possibilities for automation systems aimed at enhancing energy efficiency in both home and office settings. This study focuses on the creation and deployment of an IoT-driven Smart Home system utilizing ESP32 for the automatic and manual supervision and regulation of electrical appliances within the Employee Dormitory of the Institute for Lecturer Performance Development (LPKD). The established system employs a Passive Infrared (PIR) sensor for detecting human presence and a Light Dependent Resistor (LDR) sensor to assess the intensity of light in the room. The data from these sensors is analyzed by the ESP32 microcontroller, which controls lights and fans automatically through relay modules based on the surrounding conditions. Furthermore, the system is linked to the Blynk application and the Telegram Bot API to enable remote operation and immediate notifications. The methodological approach taken in this research is Research and Development (R&D) employing a prototyping method. The assessment outcomes show that the system functions reliably, with success rates for sensor detection and appliance management exceeding 95%. The introduction of this system aims to boost electrical energy efficiency, improve user experience, and facilitate the adoption of IoT-centered smart facility management within the LPKD framework.

The surge in young investors in the country indicates that university students are increasingly drawn to the financial markets. Unfortunately, the soundness of students' investment choices often lacks a foundation of clear reasoning, as they remain swayed by social influences, limited insight, and the rapid technological advancements that facilitate access to investment opportunities. This study aims to unravel the determinants of students' investment decisions through the lens of the Theory of Planned Behavior (TPB), focusing on financial literacy, risk tolerance, and technology—three factors frequently examined in existing literature. A qualitative approach was adopted, involving a literature review of scholarly articles published between 2020 and 2024. Data gathered from relevant academic sources were analyzed using content analysis techniques to identify research patterns, conceptual relationships, and the consistency of prior findings. The results reveal that the Theory of Planned Behavior effectively explains students' investment decisions through the interplay of attitudes, subjective norms, and perceived behavioral control. Financial literacy emerges as the most robust and consistent determinant influencing investment decisions; risk tolerance shapes investment preferences; and technology acts as a catalyst, enhancing accessibility and convenience. These findings suggest that deepening financial literacy—supported by optimal technology use and adequate risk awareness—can empower students to make investment decisions that are rational, well-calculated, and long-term oriented.

This research was conducted at Toko Bangunan Jaya Perkasa. The purpose of this study is to determine whether the internal control system for inventory management in the observed company has been implemented effectively or not. This study uses a qualitative method with data source triangulation techniques, including observation, interviews, and documentation based on data collection and relevant facts. The research informants consisted of seven individuals. The results show that the internal control system at Toko Bangunan Jaya Perkasa has not been implemented optimally, and the inventory management is still vulnerable to risks and potential losses. This is due to the fact that the procedures for purchasing, storing, recording, and selling goods are still conducted manually. The company faces several problems such as stock discrepancies, damaged goods, and obstacles related to suppliers and customers. The suggestions provided include implementing a computerized system for inventory management in the future, conducting regular stock opname to minimize stock discrepancies, improving communication to avoid duplicate stock records, and establishing clear communication and agreements at the beginning of transactions to overcome external constraints.