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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.

This study evaluates the efficiency of two artificial intelligence models, DeepSeek and OpenAI, in generating code for algorithmic systems. Efficiency is assessed through execution speed, code accuracy, and the number of code characters produced. Data were collected from 100 tests covering search, sorting, graph, dynamic programming, optimization, data processing, text, and machine learning algorithms. The objective is to compare the performance of both models to support the development of efficient information retrieval systems. The method involves algorithm testing with statistical analysis of execution time, accuracy, and code length. Results indicate that DeepSeek has an average execution time of 28.74 seconds, slightly slower than OpenAI’s 28.49 seconds. However, DeepSeek’s accuracy (85.88%) surpasses OpenAI’s (85.03%). The average number of code characters is identical at 96.35 characters. The study concludes that DeepSeek excels in accuracy, while OpenAI is faster in certain cases, providing valuable insights for developers in selecting AI models for information retrieval applications.

Credit card fraud is a critical issue in digital financial transactions. This study aims to develop and evaluate fraud detection models using Logistic Regression and Gradient Boosting on an imbalanced dataset, where fraudulent transactions constitute only a small portion of the data. To address this imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied during preprocessing. Logistic Regression, used as a baseline model, achieved 95% accuracy, 78.6% precision, 55.9% recall, and a 65.3% F1-score. After applying class weighting and SMOTE, recall improved to 88.7%, but precision dropped to 52%, indicating that the model became overly sensitive and prone to false positives. Gradient Boosting initially produced better results, with 98% accuracy, 95.5% precision, 84.3% recall, and an 89.5% F1-score. After hyperparameter tuning and resampling, its performance improved further to 96.7% precision, 86.1% recall, and a 91.1% F1-score. These results indicate that Gradient Boosting is more effective in handling imbalanced data and offers greater reliability in detecting fraudulent transactions. The findings support the growing evidence in favor of ensemble learning techniques in fraud detection applications. This research contributes practical insights into improving the accuracy and security of machine learning-based fraud detection systems in financial services.

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 community service was carried out at SMAS PGRI 1 Mojokerto City with the main goal of improving student discipline through the application of Japanese-style discipline culture. This activity is designed in a structured manner to have a real and sustainable impact on student behavior and the integrity of educational institutions. The method used is a participatory and applicative approach, so that students not only passively receive information, but also actively engage in the process of learning, reflection, and discipline practice. This approach emphasizes the direct involvement of students in activities that foster awareness, responsibility, and positive habits that support the creation of a conducive learning environment. The results of the implementation of activities are divided into three main categories. First, the short-term results seen immediately after the activity are increased students' motivation and understanding of the importance of discipline. Second, the medium-term results that appear within 1-3 months are in the form of real behavioral changes, such as punctuality, neatness, and compliance with school rules. Third, long-term results that contribute to strengthening the integrity of the institution as a school with a high discipline image. Thus, this community service is expected to be able to become a model for implementing a discipline culture that is effective, sustainable, and relevant to the needs of education in Indonesia.

This community engagement program aims to strengthen the halal value chain of micro, small, and medium enterprises (MSMEs) in Hagu Selatan Village, Banda Sakti District, Lhokseumawe City through knowledge transfer based on the Indonesian halal value chain model. MSMEs play a vital role in regional economic development, yet many still face challenges in understanding halal–thayyiban principles, fulfilling certification requirements, managing production processes, and accessing Islamic financing. Limited adoption of digitalization also reduces their competitiveness in the rapidly growing halal industry. The program applies a participatory approach by involving universities, village authorities, and MSMEs. Key activities include needs assessment, training on halal value chain concepts, technical assistance for halal certification documents, workshops on digital business practices, and business clinics on Islamic financing. A Halal Value Chain Learning Circle is also established to support continuous collaboration and knowledge sharing. The program is expected to enhance MSME capacity, improve product quality, expand market access, and contribute to a sustainable halal ecosystem in Aceh.

Infectious diseases remain a dynamic and evolving public health threat, requiring data-driven approaches for early detection and targeted policy planning. This study aims to model spatio-temporal trends and clustering patterns of HIV transmission in Bogor Regency during the period 2020–2023 by utilizing a combination of unsupervised and supervised machine learning techniques. The dataset was obtained from the Bogor Regency Health Office and includes annual data on the number of HIV cases across 40 sub-districts. The research methodology consists of data preprocessing stages, clustering using the K-Means algorithm, and classification using a Decision Tree model. The preprocessing steps include data integration, attribute selection, temporal aggregation, handling of missing data, and normalization using Z-score. K-Means clustering is applied to identify hidden patterns in the development of HIV cases, resulting in three distinct clusters based on multi-year trends. The resulting cluster labels are then used as target classes in the supervised classification process. The Decision Tree classification model demonstrates high accuracy in predicting cluster membership, indicating a strong relationship between the temporal patterns of HIV cases and cluster identity. The integration of clustering and classification techniques provides a robust analytical framework for understanding the dynamics of HIV transmission, while also supporting the formulation of more precise, evidence-based, and region-specific public health interventions.

This study aims to analyze the implementation of the Balanced Scorecard (BSC) as a strategic performance evaluation tool in the era of digital transformation. Using a descriptive qualitative approach within the social constructivist paradigm, data were collected through in-depth interviews, non-participant observation, and document analysis in three organizations undergoing digitalization. Thematic analysis (Braun & Clarke, 2006) identified four main themes in the application of the BSC: digital strategy alignment, digital readiness and data integration, a culture of learning and innovation, and adaptive leadership transformation. The findings indicate that the BSC functions not only as a performance measurement system but also as an adaptive, collaborative, and data-driven strategic management framework. The integration of digital technologies accelerates decision-making processes and strengthens reflective organizational culture. Theoretically, this study extends the classical BSC model of Kaplan and Norton (1996, 2001) toward a Digital Balanced Scorecard that emphasizes synergy among strategy, data, and organizational learning. Practically, the results highlight the importance of digital readiness, an innovation-oriented culture, and adaptive leadership as key foundations for successful BSC implementation in the era of digital disruption.

This study aims to examine the strengthening of school literacy culture through the establishment of a Literacy Corner at SMPN 4 Mangarabombang as a strategy to enhance students’ reading interest and engagement in literacy activities. The research problem arises from students’ low reading intensity and the limited availability of literacy-supporting facilities at school. A qualitative descriptive method was employed, utilizing observation, interviews, and documentation as data collection techniques. The findings indicate that the Literacy Corner significantly improves students’ access to reading materials, fosters more consistent reading habits, and creates a more conducive learning environment. Moreover, the involvement of teachers and students in managing the Literacy Corner strengthens their sense of ownership and increases active participation in school literacy activities. By facilitating a space dedicated to reading, the initiative addresses the challenges related to the scarcity of resources and encourages students to make reading a regular activity. Teachers also reported increased student motivation and engagement in literacy programs, which translates into greater academic performance. These results highlight that establishing a Literacy Corner is an effective and strategic approach to reinforcing school literacy culture. Furthermore, it can serve as a model for other schools aiming to enhance their literacy programs and improve student engagement in reading activities.

Arabic grammar (nahwu) instruction has long been dominated by rule-based approaches that emphasize memorization and formal analysis, often resulting in rigid learning structures and limited responsiveness to learners’ cognitive diversity. While such approaches play an important role in preserving grammatical accuracy, they frequently overlook individual learning trajectories, cognitive readiness, and adaptive instructional needs. In the era of artificial intelligence (AI), language education is increasingly shaped by adaptive learning systems that personalize content, pacing, and instructional strategies based on learners’ profiles. This study aims to reconceptualize Arabic grammar instruction by proposing a conceptual framework that integrates traditional nahwu principles with adaptive learning systems informed by AI. Using a qualitative conceptual analysis, this paper synthesizes classical Arabic grammar pedagogy, contemporary theories of adaptive learning, and recent developments in AI-supported language instruction. The proposed framework highlights key components, including learner profiling, cognitive-level alignment, hierarchical nahwu content structuring, and AI-assisted scaffolding mechanisms. The findings suggest that adaptive learning systems offer significant pedagogical potential to transform nahwu instruction from a static, rule-centered model into a flexible, learner-centered process. This reconceptualization is expected to enhance grammatical comprehension, reduce cognitive overload, and promote learner autonomy in Arabic language education, particularly in Islamic higher education contexts. The study concludes by discussing pedagogical implications and directions for future empirical research on AI-assisted Arabic grammar learning.

Islamic Religious Education (PAI) faces serious challenges from the crisis of integrity and trust in the digital era, which is manifested in the weakening of social solidarity (ukhuwah) and the emergence of a toxic social environment due to disinformation and fragility of commitment. This study aims to analyze and formulate an implementation model for the values ​​of Shiddiq (honesty and truth) and Amanah (trustworthiness and responsibility) in PAI, as well as to examine their role in building Ukhuwah and a Positive Social Environment among students. The method used is library research with a qualitative-analytical approach, involving a critical review of relevant scientific literature, journals, and books. The results of the study indicate that the implementation of these two prophetic values ​​must be carried out transformatively through integrated Project Based Learning (PjBL) and Problem Based Learning (PBL) methods, not merely cognitive transfer, but through real practice. The value of Shiddiq plays a central role in building trust and countering hoaxes, while Amanah ensures commitment and social responsibility, which collectively strengthen the bonds of ukhuwah. These findings imply the urgency of developing an Islamic Religious Education (PAI) curriculum that is responsive to digital ethics and strengthens teacher exemplary behavior (uswah hasanah) as a model of integrity. It is recommended that future research conduct empirical tests of the proposed implementation model to strengthen the generalizability of the findings.

This study explores the integration of Science, Technology, and the Arts (IPTEKS) within an educational psychology framework to support the development of creativity, innovation, and collaboration among prospective Christian religious education teachers in West Java. Using a mixed-methods approach with a sequential explanatory design, the research combines quantitative and qualitative perspectives to obtain a comprehensive understanding of the phenomenon. Quantitative data were gathered through questionnaires distributed to prospective teachers, while qualitative data were obtained through in-depth interviews and participatory observations involving selected informants. The findings indicate that meaningful integration of IPTEKS contributes positively to the development of creative thinking, innovative teaching practices, and collaborative learning skills. Qualitative insights further reveal that institutional support, continuous professional development, and contextualized learning environments play a crucial role in optimizing the impact of IPTEKS integration. The study highlights the importance of aligning technological integration with psychological and pedagogical principles. It concludes that teacher education programs need to redesign curricula and training models that holistically integrate IPTEKS and educational psychology to foster relevant, transformative, and value-based learning in Christian education contexts.

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

This study aims to describe teachers' strategies in developing early childhood language skills at the AS-SA'ADAH Early Childhood Education Centre. It is known that strategies are importantThis appears to be part of a larger context, likely related to educational development teachers must have ideas on how to design and implement these strategies using a descriptive qualitative approach with data collected through direct observation of learning activities, interviews, and documentation. The analysis was conducted using the Miles and Huberman model, which includes the stages of reduction, presentation, and conclusion drawing. The results of the study show that teachers develop children's language skills through storytelling, interactive conversations, singing, and the use of self-made pictures and simple teaching aids. Based on interviews, these strategies not only enrich the vocabulary of early childhood language but also encourage children to be more active in speaking and interacting with their peers and teachers. Language learning associated with educational play activities has been proven to be more interesting for children in the learning process so that it seems natural, because most children tend to get bored with monotonous learning processes. Thus, children's language skills can grow and develop optimally if a teacher is creative, patient, and communicative learning environment.

This study aims to analyze the implementation of the Independent Curriculum in third-grade students at Al-Munawarah Elementary School, Sentani, Jayapura Regency. Using a qualitative approach with data collection techniques through observation, interviews, and documentation, this study evaluated three main aspects: planning, implementation, and evaluation of learning. The results showed that during the planning stage, teachers developed teaching modules that referred to Learning Outcomes (CP) and prepared assessment instruments in the form of projects and prompt questions. During the implementation stage, teachers implemented an inquiry-based learning model to encourage student engagement and utilized various media, from printed books to digital devices, which positively impacted student engagement in class. During the evaluation stage, teachers used cultural project assessments and Student Worksheets (LKPD), accompanied by positive feedback to motivate students. Although implementation generally proceeded according to the curriculum framework, obstacles were still encountered in the application of differentiated learning because teachers tended to use lecture methods and generalize the abilities of all students. Therefore, continuous improvement is needed so that learning planning can be more aligned with the characteristics and individual needs of each student.

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

This study examines the implementation of an Islamic Religious Education (PAI) learning model based on Project-Based Learning (PjBL) and collaborative approaches in shaping students’ noble character at SD Negeri Besuk Kidul, Besuk District. The study is grounded in the research gap that PAI learning in elementary schools is often still dominated by conventional, teacher-centered methods that emphasize cognitive achievement while providing limited space for the internalization of moral values through authentic learning experiences. This research aims to analyze how PjBL and collaborative learning are designed and implemented in PAI instruction and to explore their contribution to students’ character development. A qualitative approach with a descriptive case study design was employed. The research subjects included the school principal, a PAI teacher, and elementary school students. Data were collected through observation, in-depth interviews, and documentation, and analyzed using an interactive data analysis model. The findings reveal that the integration of project-based and collaborative learning in PAI instruction enhances students’ noble character, particularly in terms of honesty, discipline, responsibility, cooperation, respect, and social awareness. Students actively engage in learning activities, apply Islamic values in real-life contexts, and demonstrate positive behavioral changes both in and outside the classroom. These results indicate that Project-Based Learning and collaborative approaches constitute an effective and meaningful strategy for strengthening character education in PAI at the elementary school level.

The professional competence of Islamic Education (PAI) teachers plays a decisive role in determining the quality of learning at the elementary school level. In practice, many teachers still encounter challenges in mastering subject content, developing systematic teaching materials, applying innovative learning strategies, and integrating educational technology into classroom activities. These conditions indicate the need for structured professional development efforts through collaborative forums. This study aims to analyze the role of the Islamic Education Teachers Working Group (KKG PAI) in maximizing the professional competence of PAI teachers in public elementary schools in Panti District, Pasaman Regency, and to identify the supporting and inhibiting factors influencing its implementation. This research employed a qualitative approach with a case study design. Data were collected through in-depth interviews, participatory observation, and documentation involving the KKG supervisor, the head of KKG PAI, and member teachers. Data analysis was conducted using an interactive model consisting of data reduction, data display, and conclusion drawing. The findings reveal that KKG PAI functions as a strategic platform for collaborative lesson planning, subject-matter enrichment, peer reflection, and technology-based instructional training. Supporting factors include strong teacher commitment and collaborative culture, while limitations in facilities and technological disparities remain challenges. Strengthening the sustainability and management of KKG programs is essential to enhance teachers’ professional competence and improve the overall quality of Islamic education learning.

This study examines the role of Islamic Religious Education in shaping the character of young generations in the contemporary era. Islamic Religious Education is not only focused on cognitive aspects but also emphasizes moral, spiritual, and social development. The rapid development of technology and globalization has influenced the lifestyle and mindset of youth, creating challenges in maintaining ethical values and noble character. This research aims to analyze how Islamic Religious Education contributes to the formation of students’ character, including honesty, responsibility, discipline, tolerance, and social awareness. The research method uses a qualitative descriptive approach through literature review and analysis of relevant educational practices. The results show that effective Islamic Religious Education can strengthen students’ moral awareness, develop positive behavior, and build spiritual intelligence. Teachers play a significant role as role models in integrating Islamic values into daily life. Therefore, strengthening curriculum, learning methods, and collaboration between schools, families, and communities is essential to optimize the role of Islamic Religious Education in forming a morally upright and responsible young generation.

The Qur’an and Hadith, as the primary sources of Islamic teachings, provide a comprehensive value framework regarding the ideal character that should be possessed by both educators and learners. Educators are required to demonstrate sincerity, patience, justice, noble character, and to serve as role models (uswah hasanah) for their students. Education is a fundamental pillar in the formation of individual character and personality. This study aims to examine and analyze the concepts of attitudes and personality of educators and learners based on the Qur’an and Hadith. The method employed is a literature review using a qualitative approach through the analysis of relevant Qur’anic verses and Prophetic traditions. The results of the study indicate that learners are individuals who strive to develop their potential through the learning process within educational pathways, both formal and non-formal, at certain levels and types of education. Among the ethics of learners toward educators are sitting politely in front of the teacher, speaking respectfully, not interrupting the teacher while speaking, listening attentively to the teacher’s explanations, asking questions gently and respectfully when something is not understood, attending school regularly, avoiding truancy and lateness without valid reasons, entering the classroom promptly before the teacher arrives, and obeying the teacher’s advice.