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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.

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 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.

This study examines the role of Artificial Intelligence (AI) in enhancing student collaborative learning, with a particular emphasis on AI-driven feedback mechanisms and patterns of student interaction in developing effective collaborative skills. Unlike prior studies, this research highlights the mediating effect of AI-driven feedback on teamwork efficiency and overall learning outcomes in collaborative environments. An explanatory quantitative approach was applied using Partial Least Squares Structural Equation Modeling (PLS-SEM) to ensure robust data analysis. Data were collected from 112 university students who were actively engaged in AI-assisted collaborative learning activities, using a structured online survey instrument. The data were subsequently analyzed using SmartPLS software. The results reveal that AI significantly enhances student interaction (β = 0.534, p < 0.000) and improves problem-solving feedback (β = 0.620, p < 0.000), both of which contribute to significantly strengthening collaborative skills (β = 0.716, p < 0.000). However, the findings also indicate that AI alone does not directly improve collaboration without the support of structured pedagogical design and guidance. Therefore, universities should strategically integrate AI-driven feedback into Learning Management Systems (LMS) and strengthen digital literacy initiatives to optimize the effectiveness and sustainability of AI in collaborative learning contexts.

The purpose of this study was to determine the direct effect of personality characteristics and intellectual abilities on employee performance in the digital era and competence, the effect of competence on performance, and the indirect effect of personality variables and intellectual abilities on employee performance in the digital era through competence as an intervening variable in BPSDM Jambi Province. The type of research used is quantitative research with primary and secondary data. Sampling used a simple random sampling technique so that 65 employees were selected as respondents. Data collection used a questionnaire and data analysis used Smart PLS. The results of the analysis showed that personality characteristics directly affect performance and competence with a significance value of P <0.05, intellectual abilities do not affect performance and competence with a significance value of P>0.05, and competence does not affect the performance of BPSDM Jambi Province employees in the digital era with a significance value of P>0.05. Furthermore, the direct effect shows that employee competence does not mediate the influence of personality characteristics and intellectual abilities on employee performance. This shows that personality characteristics and intellectual abilities do not affect performance through employee competence as an intervening variable.

This study aims to test the influence of digital literacy and the use of accounting applications on the effectiveness of MSME information systems with user competence as a mediating variable. The research sample amounted to 100 MSME actors in Gresik City who were selected using purposive sampling techniques according to the research criteria. Data testing was carried out using a quantitative approach using the Structural Equation Modeling–Partial Least Square (SEM-PLS) method through the SmartPLS application. The results of the study show that digital literacy and the use of accounting applications have a positive effect on the effectiveness of MSME information systems. Meanwhile, user competence does not have a significant effect and is unable to mediate the influence of digital literacy and the use of accounting applications on the effectiveness of information systems. This research is expected to provide benefits for MSME actors in increasing the use of digital technology and accounting applications, as well as become an academic reference for future research. The limitations of this study lie in the scope of the MSME scale, which has not considered external factors, and the research model that has not fully explained the role of user competence as a mediating variable.

This stuidy analyzeis thei influieincei of Suistainability Reiport Disclosuirei (SRD), Good Corporatei Goveirnancei (GCG), and company sizei on firm valuiei, with profitability as a meidiating variablei, in food and beiveiragei suibseictor companieis listeid on thei Indoneisia Stock Eixchangei (IDX) duiring thei 2022–2024 peiriod. Data proceissing was peirformeid uising thei SEiM-PLS meithod with thei assistancei of SmartPLS 4.0 softwarei. Thei reiseiarch findings indicatei that SRD doeis not havei a significant impact on profitability, buit contribuiteis significantly positiveily to firm valuiei. Meianwhilei, GCG has a significant neigativei eiffeict on profitability and has no direict eiffeict on firm valuiei. Firm sizei also doeis not affeict profitability, buit has a significant neigativei eiffeict on firm valuiei. Fuirtheirmorei, profitability is provein to havei a positivei and significant eiffeict on firm valuiei and fuinctions as a meidiator in thei reilationship beitweiein GCG and firm valuiei. Howeiveir, profitability doeis not meidiatei thei reilationship beitweiein SRD and firm sizei on firm valuiei. Oveirall, thei reiseiarch reisuilts eimphasizei that profitability is thei main deiteirminant of firm valuiei, whilei SRD has a strongeir impact throuigh reipuitational aspeicts than throuigh improving financial peirformancei.

This study aims to examine the influence of advertising appeal, influencer marketing, and online customer reviews on purchasing decisions in Tokopedia’s e-commerce platform. The research applied a quantitative method using survey questionnaires distributed to 109 Tokopedia users in Jakarta. Data were analyzed using path analysis with SmartPLS. The results indicate that advertising appeal and influencer marketing significantly and positively affect purchasing decisions, while online customer reviews show no significant impact. These findings suggest that Tokopedia consumers, particularly in electronic products, are more influenced by attractive advertising and influencer endorsements than by online reviews. The study is limited by its sample size, geographic scope, and product focus on electronics. Future research is recommended to expand respondents and product categories for broader insights.

Low financial literacy among students, particularly in Islamic boarding schools, poses a challenge in fostering early economic independence. At Pondok Pesantren NW Montong Lisung, students generally lack the ability to manage pocket money, maintain financial records, and develop saving habits. This condition underlies the implementation of a community service program aimed at building smart financial habits through financial management education. The method employed a participatory approach consisting of counseling, training, and mentoring stages. Evaluation was conducted using pre-test and post-test, observation, and assessment of students’ financial record practices. The results showed a significant improvement in students’ financial literacy, increasing from an average of 42.5% to 79.5%, along with positive behavioral changes such as increased saving habits and better expense control. These findings indicate that financial management education is effective in improving students’ financial understanding and skills. Therefore, this program is important to be implemented sustainably to support the development of students’ economic independence in the future.

This study analyzes the effect of capital structure and firm growth on firm value with dividend policy as a mediating variable in property and real estate companies listed on the Indonesia Stock Exchange for the period 2019-2024. The volatility of the property sector influenced by global and domestic economic conditions encourages the importance of understanding firm value formation mechanisms. The research method uses a quantitative approach with purposive sampling technique resulting in 66 observations from 11 companies during the research period. Data analysis uses Partial Least Squares-Structural Equation Modeling through SmartPLS application to test relationships between variables. The results show that capital structure and firm growth have no direct significant effect on firm value, but have a significant negative effect on dividend policy. Dividend policy has a significant positive effect on firm value and is able to fully mediate the effect of capital structure and firm growth on firm value with Variance Accounted For values of 151.6% and 90.4% respectively. These findings confirm the importance of dividend policy as a credible signaling mechanism regarding the company's ability to generate sustainable cash flows in creating value for shareholders amid the volatility of Indonesia's property sector.  

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

The smart city concept has emerged as a primary solution to address various global urbanization challenges. However, its implementation in developing countries frequently encounters unique obstacles, such as limited infrastructure, constrained budgets, and varying levels of community readiness. This study aims to identify and analyze the critical success factors for smart city implementation in developing nations using a literature review approach. The research employs a Systematic Literature Review (SLR) method, adapting the PRISMA guidelines. Data collection was conducted by screening scientific articles from leading academic databases published over the last five years. The review results indicate that the success of a smart city in developing contexts does not rely solely on technological advancement. There are four primary dimensions acting as determinants: (1) the governance dimension, encompassing regulatory support and bureaucratic transparency; (2) the technological infrastructure dimension, involving equitable internet access and centralized data integration; (3) the human resources dimension, focusing on the digital literacy of citizens and government apparatus; and (4) the financial dimension, which includes innovative financing models and public-private partnerships. The conclusion of this review emphasizes that cross-sector collaboration and strong leadership commitment remain the most crucial foundations. These findings are expected to provide a strategic reference framework for local governments in designing more sustainable and targeted smart city roadmaps.

The development of information technology, particularly the use of smartphones, has changed human activity patterns and significantly impacted the education sector. The "one-stop-shop" concept reflects the use of mobile devices as centers for various activities, including learning. This situation drives the need for innovation in the development of adaptive and interactive learning media. One solution that can be developed is an Android-based mobile application using Flutter, which can increase the effectiveness and efficiency of the learning process. The Association of Multimedia and Information Technology Professionals (PPMultindo), an organization focused on technology, has developed an Android-based learning platform. This platform is designed to provide flexible access to materials, support interactivity, and facilitate collaboration between educators. Features such as learning analysis, material recommendations, and automatic evaluation are expected to improve the quality of the learning experience. However, the implementation of this technology still faces various challenges, including limited technological competence of educators, inadequate infrastructure, and adjustments to curriculum needs. Therefore, collaborative efforts are needed to optimize the use of mobile technology to support educational transformation in the digital era.

Limited competence among teachers in systematically managing scientific references remains one of the main challenges in producing high-quality scientific writing. This community service activity aims to enhance the competence of Biology MGMP teachers in Sidoarjo in reference management through a Smart Referencing approach using the Mendeley application as a Reference Management System. The methods employed include training sessions, hands-on practice, and mentoring in the use of Mendeley, covering installation, library management, and the automatic integration of citations and bibliographies into scientific documents. The evaluation of the activity was conducted through questionnaire distribution to measure participants’ improvement in understanding and skills. The analysis results indicate that several technical aspects, such as the use of the Mendeley plugin in Microsoft Word (score = 3.40) and the overall ease of use of the application (score = 3.00), fall into the high category on a maximum scale of 4. This suggests that although the application is perceived as useful, there is still a need for initial adaptation in its usage. Furthermore, the overall mean score of all questionnaire items is 3.74, with a satisfaction index of 93.5%, which falls into the very high category. These findings indicate that the Mendeley-based Smart Referencing training received very positive responses and was effective in improving participants’ understanding and skills in reference management for scientific writing.

Predictive maintenance (PdM) plays a crucial role in modern industrial systems by minimizing downtime, reducing maintenance costs, and optimizing asset performance. However, many predictive models operate as “black box” systems, limiting transparency and making it difficult for operators to interpret their outputs. This study aims to integrate Explainable Artificial Intelligence (XAI) techniques with Remaining Useful Life (RUL) prediction models to improve both accuracy and interpretability. Various machine learning and deep learning approaches, including Support Vector Machines (SVM), Random Forest (RF), XGBoost, Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN), are employed to predict RUL using real-time sensor data from rotating machinery. XAI methods such as SHAP, LIME, and attention mechanisms are applied to provide human-understandable explanations of model predictions. The models are evaluated based on accuracy, Root Mean Square Error (RMSE), and interpretability scores. The results show that XAI-enhanced models outperform traditional approaches in predictive performance while offering greater transparency. These explanations help maintenance engineers better understand the factors influencing predictions, thereby improving decision-making and trust in the system. Nevertheless, the integration of XAI introduces additional computational complexity, which may pose challenges for large-scale industrial implementation. Overall, this study highlights the potential of combining XAI with RUL prediction to develop more reliable, transparent, and effective predictive maintenance solutions.

This study examines the effects of word of mouth, peer influence, and promotion on exercise decisions at gymnasiums in Bandar Lampung City, with hedonic motivation as a mediating variable. Drawing on the Theory of Planned Behavior and consumer behavior perspectives, the research employed a quantitative causal-associative design. Data were collected through structured questionnaires from 100 active members of four gymnasiums and analyzed using Partial Least Squares - Structural Equation Modeling (PLS-SEM) with SmartPLS . The results indicate that word of mouth, peer influence, and promotion have positive and significant effects on hedonic motivation and on exercise decisions. Hedonic motivation also exerts a positive and significant effect on exercise decisions, suggesting that pleasurable and emotionally rewarding fitness experiences reinforce consumers' intention to engage in regular gym- based exercise. Mediation analysis further reveals that hedonic motivation significantly channels the effects of peer influence and promotion on exercise decisions, while the indirect effect of word of mouth is also significant, although its negative coefficient warrants careful interpretation. These findings demonstrate that exercise decisions are shaped not only by utilitarian health considerations but also by social influence, promotional exposure, and affective consumption experiences. The study provides practical insights for gym managers in designing service and marketing strategies that strengthen customer engagement and sustained participation.

This study is motivated by the importance of the effectiveness of the Indonesia Smart Card for Higher Education Program (KIP-K) in expanding access to higher education for students from low-income families at Universitas Negeri Gorontalo. This study aims to analyze the effectiveness of the implementation of the KIP-K Program based on the aspects of goal attainment, integration, and adaptation. The research employed a descriptive qualitative approach, with data collected through interviews, observation, and documentation. The data were analyzed through the stages of data reduction, data display, and conclusion drawing and verification. In terms of goal attainment, the program helps students continue their education, although several challenges remain, including limited quotas, inaccurate targeting, and suboptimal on-time graduation. In terms of integration, coordination among program administrators, faculties, departments, students, and banking partners has functioned quite well, although academic services for recipients have not been entirely equal. In terms of adaptation, the program has shown the ability to adjust to policy changes and students’ needs through periodic evaluation and adjustments to the disbursement mechanism. The implication is that stronger targeting accuracy, academic assistance, service quality, and evaluation systems are needed to ensure more optimal and sustainable program implementation.

This research investigates how digital transformation contributes to innovation in public services as part of the move toward smart governance. The study employs a literature review approach by evaluating a variety of pertinent materials, which include global journals, scholarly books, and official publications from the years 2018 to 2025. Results show that digital transformation notably enhances the quality of public services regarding their efficiency, effectiveness, openness, and ease of access. The incorporation of technologies like e-government platforms, mobile apps, artificial intelligence, and big data analysis allows governments to provide services that are quicker and more responsive. Additionally, digital platforms foster public involvement by offering means for communication and participation in decision-making activities. Despite these advancements, there are still several obstacles to overcome, such as the digital divide, insufficient infrastructure, low levels of digital skills, and resistance to change within bureaucracy. These issues emphasize the need for cohesive strategies that include investment in technology, development of human resources, and regulatory assistance. The study concludes that digital transformation is vital for achieving smart governance; however, its effectiveness relies on the preparedness of infrastructure, institutions, and society to embrace digital advancements.

This research is motivated by the escalating prevalence of illegal online lending practices in Indonesia, which generate a multitude of legal problems, particularly those concerning the validity of loan agreements and debt collection practices. The simplicity of access through smartphone applications, rapid processing times often approved within minutes and minimal administrative requirements have rendered these services immensely popular among the public. However, this accessibility also paves the way for unlicensed providers to operate unchecked, preying on desperate borrowers. The study aims to analyze the legal validity of illegal online loan agreements pursuant to the Indonesian Civil Code (KUHPerdata) and regulations issued by the Financial Services Authority (Otoritas Jasa Keuangan, OJK). Additionally, it examines the legal position of debt collection from a civil law perspective. A normative juridical method is employed, utilizing statutory and conceptual approaches, with qualitative analysis of the data. The results demonstrate that illegal online loan agreements fail to fulfill the requirements for a valid contract, especially regarding the legal capacity of the parties and lawful cause, categorizing them as null and void by operation of law. Nevertheless, in practice, unlicensed providers continue debt collection efforts, frequently employing methods that violate the law, such as harassment and intimidation. This reveals a significant gap between legal norms and field implementation. The implications emphasize the critical need for robust law enforcement, enhanced consumer protection mechanisms, and stricter oversight of fintech lenders to establish legal certainty and justice for society.

Litopenaeus vannamei is a brackish-water aquaculture commodity that is highly favored by the Indonesian community and represents one of the country’s leading aquaculture products, with production continuing to increase in response to rising domestic and export demand. One of the main factors triggering disease in L. vannamei is the presence of Vibrio sp. bacteria, which are recognized as serious pathogens in various aquaculture organisms and serve as causative agents of bacterial diseases. These bacteria naturally inhabit marine environments and are categorized as opportunistic, meaning they become pathogenic when environmental conditions decline and host health is compromised. Disinfectants are chemical substances used to inhibit or eliminate microorganisms such as bacteria, viruses, and fungi (excluding bacterial spores) on non-living surfaces. One disinfectant material is Smart Care (Intracare B.V., The Netherlands), which contains stabilized hydrogen peroxide with a prolonged-release mechanism. This study employed an experimental method using a Completely Randomized Design (CRD) with four treatments and five replications. The treatments included a control (without H₂O₂) and applications of H₂O₂ at concentrations of 1 ml/L, 2 ml/L, 3 ml/L, and 4 ml/L. The results indicated that the addition of hydrogen peroxide at different concentrations did not produce statistically significant differences in suppressing the growth rate of Vibrio sp. Nevertheless, treatment C (3 ml/L H₂O₂) showed the highest inhibitory effect, with no bacterial colony growth observed. Therefore, the application of H₂O₂ at 3 ml/L demonstrates potential in reducing Vibrio sp. growth and supporting sustainable shrimp aquaculture practices.