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This study aims to investigate the factors influencing the continuance intention of Al-Kautsar Senior High School students in using metaverse-based learning media. The background of this research lies in the rapid adoption of immersive technologies in education, while students’ levels of acceptance have not yet been fully understood. The objective is to identify the antecedents of satisfaction, which subsequently influence continuous intention. The research model examines the effects of perceived interactivity, perceived sociability, perceived enjoyment, perceived ease of use, perceived security, and social influence on satisfaction. A quantitative approach was employed by distributing questionnaires to students, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that satisfaction is a very strong and statistically significant predictor of continuous intention to use metaverse applications (β = 0.716, p < 0.001). The six hypothesized antecedent variables were not found to have a significant individual effect on satisfaction. In conclusion, for digital native students at Al-Kautsar Senior High School, factors such as ease of use, interactivity, and enjoyment have shifted from being drivers of satisfaction to becoming basic expectations (hygiene factors). Satisfaction itself emerges as the primary determinant, likely influenced by more substantive elements such as content quality or pedagogical design rather than merely the technical features of the platform.

Since 2022, the application of the Internet of Things (IoT) in the healthcare sector has grown significantly, marked by the increasing adoption of wearable technology, artificial intelligence (AI), machine learning (ML), and blockchain integration. Research highlights India and China as leading contributors in this domain. IoT enables real-time monitoring of chronic diseases, tracking of patient vital signs, and detection of health protocol compliance. Integrated systems such as Monit4Healthy and RADAR-IoT support personalized medical recommendations and cross-platform interoperability. However, key challenges persist, including patient data privacy and security, system interoperability issues, data fragmentation, and barriers to user acceptance due to cost, digital literacy, and device comfort. Proposed solutions include blockchain for secure data sharing, adaptive congestion control for network performance, and user training to improve technology adoption. Therefore, successful IoT deployment in healthcare requires a comprehensive approach that addresses technological, social, ethical, and sustainability aspects to achieve an effective and inclusive transformation of health services.

Behind the success of the Free Nutritious Meal Program (MBG), there are several problems related to the health factors of the program targets, namely, there are several cases of allergies that occur in schools, inadequate understanding of allergen management owned by food processing vendors, and the high cost of laboratory tests and the process that takes a long time. So, to overcome these problems, an application is proposed that can help detect allergens in food products using data mining and machine learning approaches. SVM and AdaBoost algorithms each have advantages that can be used to help build an optimal allergen detection model. This research uses a cross-validation model validation method with a value of K = 10 to help improve the performance of the model built. In this study, from the entire fold, an average accuracy value of 98.74% was obtained. To evaluate the model built, this research has also conducted several new data inputs, and in each new data input, the accuracy value is obtained above 99%. This indicates that the model built, namely the combination of SVM and AdaBoost algorithms with the cross-validation model validation method, produces high accuracy, so this model can greatly assist the allergen detection process in food products.

As a vocational education institution, SMK Swadhipa 1 Natar is required to provide adequate facilities to support the development of its students' technical and practical skills. Although some facilities are already available, student complaints remain regarding the condition, availability, and utilization of these services, particularly those related to information technology.This study aims to analyze the level of student satisfaction with information technology services at SMK Swadhipa 1 Natar using a combination of Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) methods. The study was conducted through a quantitative approach by distributing questionnaires to 100 respondents selected using stratified random sampling techniques. The data collected were analyzed to determine the overall satisfaction score and identify factors of information technology services that were a priority for improvement. The results of the CSI analysis showed that the level of student satisfaction with school information technology services was in the good category, with an average score of 82%. Furthermore, the results of the IPA analysis revealed that information technology services such as computer services in the school lab, wifi networks, and school websites consisting of school exam applications, student registration applications and information about the school on the website were in the top priority quadrant because they had a high level of importance but their performance was still low. Based on these results, it can be concluded that although in general students stated that they were quite satisfied with the information technology services available, there were several important aspects, especially technology-based information technology services, that needed more attention from the school. Thus, recommendations for improving technological infrastructure and periodic evaluation of educational information technology services can help SMK Swadhipa 1 Natar in improving the quality of educational services and student satisfaction. 

This research examines the application of the Elliptic Curve Digital Signature Algorithm (ECDSA) in a blockchain system as a security solution for digital payment systems in Indonesia. Using a descriptive-qualitative approach based on literature review and conceptual simulations using Python, this study discusses the working principles of ECDSA, its advantages over other digital signature algorithms, and the challenges of its adoption in Indonesia. The results show that ECDSA provides high cryptographic efficiency, maintains transaction authenticity and integrity, and supports a transparent decentralized system. The academic simulations include not only KYC processes, top-ups, transactions, validation by validators, and block recording, but also demonstrates the formation of an interconnected multi-level blockchain and tests scenarios for rejecting manipulated or invalid transactions. The contribution of this research lies not only in the theoretical review but also in the implementation illustrations that can be used as a basis for education and the initial development of blockchain-based digital payment systems. The research results show that ECDSA is capable of providing a high level of efficiency in the encryption and transaction verification process, maintaining data integrity and authenticity, and supporting a decentralized and transparent system. The academic simulations included the KYC process, wallet creation using ECDSA keys, balance top-ups through bank integration, transaction creation and validation, and block recording in the blockchain. Specifically, the simulations successfully demonstrated how new blocks are added to the chain by referencing the previous block's hash, as well as how transactions with corrupted signatures, manipulated amounts, or insufficient balances are automatically rejected by the validator consensus mechanism, maintaining system integrity. This research contributes not only theoretically, but also through conceptual representations that can be used as an educational foundation and for the initial development of blockchain-based digital payment systems in Indonesia.

This study compares two service management models to evaluate the governance of the Wi-Fi network in Dusun Gita Nagari Baru. The main objective is to measure user satisfaction and service quality following the implementation of the COBIT 2019 framework, particularly the DSS02 domain (Manage Service Requests and Incidents). The research employed a mixed methods approach, using historical-comparative document analysis and Likert scale questionnaires distributed to 21 active users. The data were analysed through gap analysis, capability level mapping, and descriptive statistical analysis to identify performance differences between two periods. The results indicate that most indicators in the COBIT 2019 capability model are at Level 4 (Predictable), one indicator reaches Level 5 (Optimising), and another indicator is at Level 3. Indicators directly related to the DSS02 domain, such as ease of reporting, response speed, schedule accuracy, and repair time, demonstrate the most significant improvements. These findings support the hypothesis that implementing COBIT 2019-based governance for DSS02 can enhance user satisfaction and the quality of Wi-Fi network services in rural areas. This study also provides practical recommendations for the sustainable management of digital infrastructure in areas with limited access.

Social media has become a strategic tool for the government to disseminate public information quickly, interactively, and efficiently in the digital era. The Lampung Provincial Government utilizes various social media platforms such as Facebook, Instagram, and TikTok to support public communication activities. This study aims to analyze the effectiveness of public communication by measuring the level of activity of Regional Apparatus Organization (OPD) social media accounts using the logistic regression method. Data were collected through web scraping techniques on the official OPD social media accounts and then processed using a quantitative approach. The results show that the level of social media activity influences the effectiveness of public communication and the transparency of government information. These findings are expected to serve as a basis for local governments in designing public communication strategies that are more optimal and adaptive to developments in digital technology.

This study aims to analyze the factors that influence students' interest in continuing their education to college using a machine learning approach. Data was collected through an online questionnaire completed by 727 students between July 27 and August 22, 2025, covering 23 variables consisting of respondent identity (gender, grade level, major) as well as internal and external factors such as parental support, learning motivation, and preferred type of college. The data preparation stage was carried out through column cleaning, deletion of empty data, encoding of categorical variables, and division of the dataset into 80% training data and 20% test data. The Naive Bayes algorithm of the CategoricalNB type was used because it was suitable for the categorical nature of the data. The evaluation results showed that the model was able to predict student interest with 96% accuracy. For the class of students interested in continuing their studies, the precision, recall, and F1-score values were above 0.95, while the performance in the class of students who were not interested was slightly lower due to the smaller amount of data. These findings show that Naive Bayes is proven to be effective and reliable in classifying students' interest in continuing their studies and can be the basis for decision-making in designing more targeted educational strategies.

This study aims to determine the influence of the implementation of the Independent Curriculum management and teacher teaching strategies on improving student character at SMK Negeri 1 Sangatta Utara. This study was field research with a quantitative approach. Data collection techniques used questionnaires, observation, and documentation. The study population was all 230 11th-grade students at SMK Negeri 1 Sangatta Utara, with a sample of 115 respondents drawn using Suharsimi Arikunto's formula. Data analysis used multiple linear regression. The results showed that the implementation of the Independent Curriculum management had a significant effect on improving student character by 60.85%, while teacher teaching strategies had a 15.95% effect. The coefficient of determination (R²) of 0.768 indicates that the two independent variables together contributed 76.8% to student character improvement, while the remaining 23.2% was influenced by factors outside the study. Therefore, it can be concluded that the implementation of the Independent Curriculum management has a more dominant influence than teacher teaching strategies on student character development.

Drug abuse in Indonesia is a form of social deviance influenced by psychological pressure, structural conditions, and weak social ties. This phenomenon is not only related to legal aspects but also arises as a response to stress, anxiety, and negative emotional experiences. Theories such as self-medication, escapism, Durkheim and Merton's Anomie, and Agnew's General Strain Theory suggest that drug abuse behavior can develop due to imbalanced norms, social tension, and an individual's inability to cope with life's pressures. In inmates, these factors are exacerbated by challenging social and economic experiences prior to their incarceration, increasing the risk of involvement in drug use and trafficking. This study emphasizes the need for a multidimensional approach to understanding this deviance and supporting rehabilitation and social reintegration efforts. Strengthening the roles of families, communities, and educational institutions in preventing drug abuse is crucial for providing ongoing support. A deeper understanding of the patterns of individual involvement in drug abuse is key to designing more effective prevention programs, based on psychological, social, and structural approaches to reduce the long-term impact of drug abuse on society.

Equal access to health services is a fundamental right of citizens. However, vulnerable groups such as beggars are often neglected because they do not have valid residence documents. The Medan City Government launched the Medan Berkah Health Insurance Program (JKMB) to support universal Health Coverage, allowing free health services only with a Medan ID card. This study aims to assess the implementation of JKMB on beggars in Medan City by using the implementation suitability model from David C. Korten, which emphasizes the relationship between programs, organizations, and beneficiaries. The method used is a descriptive qualitative approach, with data collection through in-depth interviews, observations, and documentation studies. Informants consisted of beggars without identity who had been disciplined by Social Services, program Implementation officers, and academics in the field of social welfare. The results showed that JKMB can only be accessed by beggars while under the supervision of Social Services, through temporary identities such as "Mr. X". After being repatriated (reunification), access to health services cannot be continued due to the absence of An ID. The Program has not been able to reach marginalized groups on an ongoing basis, and there has been no integration of cross-sector data systems. The findings expose the discrepancy between program design and Target conditions, highlighting the importance of more inclusive policy reformulation, facilitation of identity ownership, and inter-agency coordination to create equitable and sustainable health access for all citizens