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This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

In the era of the Industrial Revolution 4.0 and Society 5.0, digital technology is developing rapidly. This has prompted the world of education to make major changes in learning methods, including in Islamic Religious Education (PAI). Until now, PAI has used outdated methods. These methods are inadequate to meet the needs of children who are accustomed to technology. Therefore, there is a need for technology integration in the learning process. This study aims to determine how to use E-Learning, Learning Management Systems (LMS), and Artificial Intelligence (AI) in PAI learning. This study also aims to determine the benefits, challenges, and strategies for implementing these technologies. This study used a qualitative approach with a literature review type. Data were obtained from various sources, such as books, scientific articles, journals, and relevant documents. The results show that the use of E-Learning, LMS, and AI can improve the quality of PAI learning. E-Learning makes learning easier and more flexible. LMS helps manage learning more systematically. AI helps make learning more personalized and tailored to students' needs. However, the implementation of these technologies still faces several challenges, such as limited infrastructure and low digital skills of teachers and students. Therefore, a strategy is needed to address these challenges. This strategy includes enhancing digital capabilities, strengthening technological infrastructure, developing innovative learning media, and monitoring the use of technology based on Islamic values. This will ensure optimal integration of technology into Islamic Religious Education learning.

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.

Bullying is a serious problem that can disrupt the learning process and mental development of students, including in Islamic boarding schools. Early detection of bullying is essential to creating a safe and conducive learning environment. This study aims to apply the You Only Look Once (YOLO) algorithm to automatically detect bullying through video recordings in the environment of the SMK Skill Village Islamic School Business Boarding School. The method used involves collecting a video dataset representing various types of bullying behavior, labeling the data, and training an object detection model using the YOLOv5 algorithm. The developed system is capable of detecting and classifying bullying behavior in real- time with detection accuracy reaching [accuracy value if known]. The implementation of this system is expected to assist school authorities and boarding school administrators in monitoring, preventing, and addressing bullying incidents more quickly and effectively, while also serving as an initial step in leveraging artificial intelligence technology to create a safer and more comfortable educational environment.

Social media X (Twitter) has become the main platform for the Indonesian public to express opinions, including on the trend of 'kabur aja dulu' (let's just run away for a bit). This research aims to classify the sentiments of the public using the Naïve Bayes and Support Vector Machine (SVM) methods, and to compare the accuracy of both in sentiment analysis. Data was collected via the Twitter API with the hashtag #kaburajadulu, resulting in 2,067 tweets, which, after the cleansing process and manual labeling, left 385 data points. The analysis process followed the CRISP-DM stages, which include business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Model evaluation was conducted using a confusion matrix with accuracy, precision, and recall metrics. The classification results show that 82% of tweets have a positive sentiment and 18% negative. The Naïve Bayes algorithm achieved an accuracy of 86.49%, slightly lower than SVM, which reached 88.05%. In conclusion, Support Vector Machine is more effective in sentiment classification on public opinion data. This research contributes to the digital mapping of public opinion and recommends the development of automatic labeling methods as well as the exploration of advanced algorithms in the future.

Postpartum depression is a postpartum mental health disorder that significantly impacts maternal well-being, infant development, and family functioning. The high prevalence of postpartum depression in Indonesia is due to limited access to health services, low mental health literacy, and social stigma in the community. This indicates a significant gap between the need for maternal mental health services and the availability of existing interventions, making education a crucial component in efforts to prevent postpartum depression early. This study aims to analyze the prevention of postpartum depression in postpartum mothers through telenursing-based education and screening using the Edinburgh Postnatal Depression Scale (EPDS) in the community. A descriptive case study design was used, involving one respondent, a 25-year-old primigravida mother residing in the Bantul area. The intervention was implemented online via WhatsApp and video calls, including structured health education on postpartum psychological changes, adaptive coping strategies, and the importance of social support. The intervention also included daily remote monitoring of the respondent's condition via the WhatsApp mobile application. The EPDS was administered as a pre-test and post-test to evaluate changes in the respondent's psychological condition. The findings showed a significant decrease in the EPDS score from 16 (moderate depression) to 6 (minimal depression), indicating significant psychological improvement. These results imply that integrating EPDS screening, structured health education, and daily monitoring is an effective and accessible community-based approach to preventing postpartum depression, particularly for mothers with limited mobility and access to health services.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

This study was conducted based on the crucial role of diesel generator engines as the primary source of electrical power on board ships, making their operational reliability essential. One of the factors influencing generator engine performance is lubricating oil temperature. Excessive lubricating oil temperature may reduce lubrication effectiveness, increase friction between moving components, and lower engine efficiency. Therefore, this research aimed to identify the causes of high lubricating oil temperature in diesel generator engines and determine appropriate corrective actions. The study employed a descriptive quantitative approach. Data were collected through direct observation, interviews, and documentation during sea practice aboard MV. CL FLANDERS from 4 July 2024 to 5 July 2025. The data were analyzed using simple linear regression to examine the relationship between generator load and lubricating oil temperature. The findings revealed that generator load had a significant effect on the increase in lubricating oil temperature. Under normal operating conditions, the lubricating oil temperature ranged from 60°C to 72°C, while under abnormal conditions it increased to between 68°C and 81°C. The abnormal rise in temperature was mainly caused by cooling system problems, particularly a dirty LO cooler, scale deposits on the sea water pump impeller, and blockage in the cooling capillary pipes. The regression equation under normal conditions was Y = 45 + 0.30X, whereas under abnormal conditions it was Y = 53.5 + 0.30X. Elevated lubricating oil temperature resulted in lower oil viscosity, higher fuel consumption, and reduced diesel generator engine performance. Therefore, regular maintenance of the LO cooler, sea water pump, and continuous temperature monitoring are necessary to maintain optimum engine performance.

Public Wi-Fi services (Wifi_STAKat) at the State Catholic College of Pontianak continue to face technical issues, such as network speed and connection stability, as well as non-technical challenges, including the responsiveness of administrators to user complaints. This study aims to analyze user satisfaction based on the five Servqual dimensions and to map improvement priorities using the Importance–Performance Analysis (IPA) method. The relationship between Servqual and IPA is explained by mapping GAP values (perception–expectation) into the four IPA quadrants to determine the urgency level of service improvements. A 4-point Likert scale was used to avoid neutral responses and strengthen the clarity of respondents’ perceptions. The results show that all dimensions have negative GAP scores, particularly responsiveness and reliability, which are directly related to technical indicators (speed, stability, coverage) and non-technical factors (responsiveness to complaints, ease of access. The study recommends integrating an IT-based monitoring system and increasing network capacity to improve service quality.

This study aims to improve subcontractor safety performance through strengthening governance systems, leading safety indicators, capability building, and performance monitoring at PT Putra Perkasa Abadi (PPA) Jobsite Borneo Indobara (BIB). The research was motivated by the increasing trend of subcontractor incidents during Quarter 1 to Quarter 3 of 2025, where seven incidents occurred and exceeded the company threshold. In addition, subcontractor performance evaluation scores remained below the target threshold of 70, while customer satisfaction scores in subcontractor management decreased from 8.45 to 7.58. The study applied a continuous improvement approach using Quality Control Circle (QCC), Pareto analysis, Nominal Group Technique (NGT), and root cause analysis with the Ishikawa method. Improvement initiatives were implemented through four strategic pillars: strengthening governance, reinforcing leading indicators, capability building, and integrated dashboard monitoring. The implementation results showed significant improvements in subcontractor safety management. The subcontractor incident frequency rate was reduced to zero incidents in Quarter 4 of 2025, subcontractor performance evaluation increased above the threshold to 70.81, and customer satisfaction scores improved to 8.55. The findings indicate that structured governance strengthening combined with real-time monitoring and subcontractor engagement can significantly improve mining safety performance and stakeholder trust.

This study aims to analyze the implementation of the Bravo PUPR Online attendance system in improving the work discipline of Civil Servants (ASN) at the National Road Implementation Center of East Nusa Tenggara. The research focuses on punctuality of attendance, consistency in fulfilling working hours, task completion, compliance with attendance procedures, alignment between recorded data and actual conditions, and acceptance of consequences for violations. The study employs a qualitative approach with data collection techniques including observation, documentation, and interviews with leaders, system operators, and ASN as direct users. The results indicate that the implementation of the Bravo PUPR Online attendance system has improved administrative order in attendance and increased ASN awareness of time discipline. However, work discipline has not been fully optimal, as several issues remain, such as inconsistent attendance, suboptimal fulfillment of working hours, and discrepancies between attendance data and actual field conditions. In addition, technical constraints such as internet connectivity and GPS accuracy, as well as behavioral factors like negligence and lack of supervision, also affect system effectiveness. In terms of compliance, the Bravo system integrated with e-HRM is considered effective in detecting violations and enforcing strict consequences, ranging from warnings to administrative sanctions. This demonstrates that the attendance system functions not only as a recording tool but also as an instrument for monitoring discipline.

This study discusses the design and testing of a growing media moisture and water level monitoring system based on ESP32-MQTT. The system was developed to support real-time monitoring of growing media conditions and water availability through a monitoring dashboard. This research used an experimental method with a design and implementation approach by developing an ESP32 circuit connected to a capacitive soil moisture sensor and a water level sensor, then sending sensor data to the dashboard through the MQTT protocol and Node-RED. Testing was carried out using a plant pot as the moisture testing medium and a water container as the water level testing medium. The results showed that the growing media moisture sensor displayed 0% in dry and very dry soil conditions, 61% in moist soil, and 89% in very moist soil. The water level sensor displayed 0 cm, 2.4 cm, and 4 cm according to the testing conditions. These results indicate that ESP32-MQTT can be used as an initial prototype for monitoring growing media moisture and water level before being applied to a complete hydroponic or aquaponic system.

This article analyzes the legal status of golf course development, specifically Gunung Geulis Country Club (GGCC) in the Puncak-Bogor Area within Indonesia's spatial planning policy and Green Open Space (RTH) protection framework, while evaluating its ecological impacts from an environmental justice perspective. Employing a normative juridical method with statutory, conceptual, and case-based approaches, this research identifies two core issues. First, golf course development occupies a legal grey area: it is recognized as private RTH under Article 29(2) of Law No. 26 of 2007 on Spatial Planning, yet substantively fails to fulfill the ecological functions mandated by law due to its exclusivity and inaccessibility to the public. Second, from an environmental justice perspective, GGCC's development generates layered distributive, procedural, and corrective injustices: surrounding communities bear the burden of groundwater contamination, reduced spring discharge, increased surface runoff, and flood risk, while economic and recreational benefits are concentrated among a small number of high-fee members. Weak AMDAL instruments, minimal public participation, and inconsistent spatial monitoring in the Puncak-Bogor protected area exacerbate these conditions. This article recommends policy reforms including stricter private RTH definitions, strengthened participatory AMDAL processes, and consistent application of the polluter-pays principle.

This study aims to explore issues faced by students and the contribution of guidance and counseling (BK) services in addressing various challenges at MTSN Cirebon. The issues studied include low levels of discipline, school withdrawal behavior, lack of learning motivation, and smoking habits among students. This study employed a qualitative, descriptive approach. Participants in the study consisted of BK teachers, students, and student organizations (OSIM and MPK) selected using a purposive sampling technique. Data were collected through in-depth interviews, observation, and documentation. Data analysis was conducted using an interactive model involving data reduction, data presentation, and conclusion drawing. Its validity was tested through triangulation of sources and techniques. The findings of this study indicate that the issues faced by students are influenced by internal and external factors, such as lack of self-awareness, low learning motivation, environmental impacts, and excessive use of social media. BK services play a vital role in addressing these issues through preventive and curative approaches, as well as collaboration between teachers, students, parents, and school organizations. In addition, consistent discipline, engaging learning methods, and monitoring of student behavior are also crucial elements in problem-solving efforts. This research confirms that resolving student issues requires a comprehensive and collaborative approach across all parties within the school environment. Guidance and counseling services play a strategic role in supporting students in overcoming challenges and developing their full potential.

Citizen Lawsuit (CLS) is a legal instrument through which citizens file lawsuits against the government for its negligence in fulfilling and protecting public rights. This study aims to analyze juridically the ruling in the CLS case concerning Jokowi’s diploma based on Decision Number 211/Pdt.G/2025/PN Skt. The method employed is normative legal research using both the statute approach and the case approach. Primary legal materials consist of court decisions, while secondary legal materials include relevant literature, journals, and legal doctrines. The findings indicate that the judges’ considerations in this case focused on the plaintiff’s legal standing and the government’s responsibility to fulfill citizens’ rights. The judges appear to have adopted a more progressive perspective in assessing state responsibility, although the implementation of the ruling still faces obstacles due to difficulties in effective enforcement. This study emphasizes the strategic role of CLS as a mechanism for monitoring public policy while also highlighting the urgency of strengthening regulations and ensuring consistency in judicial decisions to provide optimal protection of citizens’ rights.

This study aims to examine the effect of debt policy and transfer pricing on tax avoidance, with audit quality as a moderating variable. The object of this study is non-banking companies included in the LQ45 index listed on the Indonesia Stock Exchange during 2021-2024, with a total sample of 117 firm-year observations. The data were analyzed using multiple linear regression and subgroup analysis (and chow test), by comparing the regression results between companies audited by Big Four and non-Big Four audit firms. The results indicate that debt policy has a positive and significant effect on tax avoidance, while transfer pricing does not have a significant effect on tax avoidance. Audit quality is proven to moderate the relationship between debt policy and tax avoidance by weakening the effect. However, audit quality does not moderate the relationship between transfer pricing and tax avoidance. These findings suggest that corporate financing decisions through debt remain an important mechanism in tax planning practices, while audit quality plays a crucial role as an external monitoring mechanism in limiting aggressive tax avoidance behavior.

This study aims to analyze the effect of Knowledge Sharing and Knowledge Leakage on Supply Chain performance, with Monitoring Opportunity as a mediating variable at the Library Office of Mesuji Regency. The research problem arises from the limited structure of knowledge-sharing practices, weak documentation of organizational knowledge, and the potential risk of knowledge leakage that may disrupt the effectiveness of library service supply chains. This study employs a quantitative approach using a survey method. Data were collected through questionnaires distributed to 115 employees of the Library Office of Mesuji Regency and analyzed using Structural Equation Modeling based on Partial Least Squares with SmartPLS. The results show that Knowledge Sharing has a positive and significant effect on Supply Chain performance and Monitoring Opportunity. Knowledge Leakage does not have a significant direct effect on Supply Chain performance, but it has a negative and significant effect on Monitoring Opportunity. Furthermore, Monitoring Opportunity significantly mediates the relationship between Knowledge Sharing and Supply Chain performance, but does not mediate the relationship between Knowledge Leakage and Supply Chain performance. These findings indicate that knowledge sharing becomes more valuable when supported by monitoring capability, while knowledge leakage should be controlled through documentation, access control, and knowledge protection mechanisms. This study contributes to knowledge management and supply chain literature in public library service organizations.

The Village Fund Direct Cash Assistance Program (BLT-DD) is a social protection instrument designed to help low-income families meet their basic needs. However, its implementation often faces challenges such as targeting inaccuracies, limited data, and varying administrative capacity at the village level. This study aims to evaluate the implementation of BLT-DD using William N. Dunn’s six policy evaluation criteria through a Systematic Literature Review (SLR) approach, covering effectiveness, efficiency, equity, responsiveness, conceptual alignment, and implementation. The findings indicate that BLT-DD is fairly effective in helping households maintain consumption, yet its effectiveness and adequacy remain constrained by the amount of assistance and the quality of data collection. Program efficiency and responsiveness are relatively good in villages with sufficient governance capacity, while equity emerges as the weakest aspect due to inaccurate data verification. Conceptually, BLT-DD aligns with the needs of low-income communities, but implementation accuracy still requires reinforcement. Furthermore, the study highlights the need for more systematic monitoring mechanisms, cross-sectoral data integration, and administrative training for village officials to enhance service quality. Overall, BLT-DD provides valuable support but requires improvements in governance and data systems to optimize outcomes, including regular evaluation strategies and refinement of supporting regulations.

Critically ill patients are individuals with unstable health conditions who require close monitoring of hemodynamic parameters. The high mortality rate among critically ill patients treated in intensive care units reaches 36.5% of 33,148 patients. Hemodynamic instability in critically ill patients can be influenced by underlying diseases, medical interventions, as well as physical and psychological stress responses during treatment. Therefore, in addition to pharmacological therapy, non-pharmacological interventions such as Asmaul Husna dhikr therapy are needed, as they can provide a relaxation effect and help stabilize hemodynamic parameters in critically ill patients. To determine the outcomes of the implementation of Asmaul Husna dhikr therapy. This study used a descriptive case study method involving two critically ill patients with unstable non-invasive hemodynamic parameters. Changes in non-invasive hemodynamic parameters were observed in both respondents after the implementation of Asmaul Husna dhikr therapy. In respondent 1, the hemodynamic status was initially categorized as increased and became stable after the intervention. Similarly, in respondent 2, the hemodynamic status changed from increased before the intervention to stable after the intervention. The implementation of Asmaul Husna dhikr therapy can be used as a complementary therapy to help stabilize hemodynamic parameters in critically ill patients.

Pressure ulcers are a common complication in patients with impaired consciousness due to prolonged immobilization. This condition can increase morbidity and prolong the length of stay, thus requiring effective preventive interventions such as progressive mobilization. To determine the outcomes of implementing progressive mobilization on the incidence of pressure ulcers in patients with impaired consciousness at the Anggrek 2 High Care Unit (HCU) of Dr. Moewardi General Hospital. This study employed a case study design involving two participants with impaired consciousness. The intervention, consisting of progressive mobilization, was conducted over 3 days with monitoring of skin condition and pressure ulcer risk. Findings: Following the implementation of progressive mobilization, both participants showed improvement in skin condition and a reduction in the risk of pressure ulcers, as evidenced by the absence of progression to more severe wounds and an increase in skin integrity. The application of progressive mobilization is effective in preventing and reducing the risk of pressure ulcers in patients with impaired consciousness. This intervention can serve as a safe and planned nursing intervention in the intensive care unit.