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This community service activity aims to improve lecturers' competence in supervising master's student thesis proposals through interactive workshops and intensive mentoring at the Adias Institute of Technology and Business, Pemalang. The activity was carried out in two online sessions via Zoom Meeting on April 11 and May 21, 2026, involving 24 participants consisting of 12 active supervisors and 12 master's students. The approach used refers to Kolb's experiential learning model, including socialization of needs, workshops on academic standards and feedback techniques, mentoring simulations, and formative evaluations based on competency rubrics. The results of the activity showed a significant increase in all indicators of mentoring competence with an average increase of 51.7 percent. All 12 lecturers successfully developed structured mentoring plans, and 24 student proposals reached the seminar-ready stage. Theoretically, these findings strengthen the relevance of the experiential learning approach in developing lecturers' academic competence. Practically, this program provides a replicable intervention model for private universities in standardizing the quality of thesis supervision at the master's level.

This study explores Indonesian EFL student teachers’ experiences of learning to write news articles through blogging in a Journalism course. The study was motivated by the need to provide meaningful and genre-based writing practice for EFL student teachers, who often face difficulties in generating ideas, organizing information, meeting genre expectations, and writing for authentic aences. Employing a qualitative case study design, the study involved twenty undergraduate student teachers from a private Islamic university in Tangerang, Indonesia; all participants completed an online quetaire, and five volunteers joined follow-up semi-structured interviews. The questionnaire data were alysed descriptively, while the interview data were examined thematically. The findings indicate that blogging supported regular writing practice, helped students understand news text structure, enouraged clearer organization of headlines, leads, and supporting details, and increased engagement by allowing students to publish and share their work. Blogging also promoted peer interaction and selfevaluation because students could read, compare, and comment on one another’s posts. However, some paticpants eprienced challenges related to technical blogging skills, uncertainty about writing standards, limited peer feedback, and discomfort with public online publication. The study concludes that blogging can serve as a useful platform for EFL news writing when it is supported by explicit istrucion, relevant tasks, clear assessment criteria, structured feedback, and ethical awareness in using digital and AI-driven tools.

Antimicrobial resistance is a persistent threat to hospital care, particularly when empirical therapy relies on broad-spectrum antibiotics without continuous evaluation of local use and susceptibility patterns. This literature review aimed to synthesize evidence from four Indonesian hospital-based studies regarding antibiotic utilization, rationality assessment, and bacterial resistance profiles. A structured narrative review was conducted using four selected articles provided by the author. Data were extracted for study design, setting, population, antibiotic evaluation method, dominant antibiotic classes, rationality indicators, resistance profile, and stewardship implications. The four studies were descriptive and hospital-based, using retrospective records, concurrent observation, ATC/DDD with DU 90%, qualitative rationality criteria, and antibiogram data. The synthesis showed a consistent concentration of antibiotic use in broad-spectrum groups, especially third-generation cephalosporins, penicillins, quinolones, and macrolides. In a Bandung public hospital, total antibiotic consumption reached 95,719.01 DDD, with penicillins, cephalosporins, quinolones, macrolides, and sulfonamides included in the DU 90% segment. In intensive care, ceftriaxone was the most frequently used antibiotic and most rationality indicators were appropriate, although clinically significant drug interactions were still identified. In pediatric acute respiratory infection inpatients, cefotaxime and ceftriaxone dominated empirical therapy. Resistance mapping in Denpasar highlighted relevant Gram-positive and Gram-negative pathogens and recommended antibiotics according to susceptibility levels. Overall, the reviewed evidence supports an integrated antimicrobial stewardship model combining ATC/DDD-DU 90% surveillance, qualitative rationality evaluation, antibiogram-based empirical guidance, and periodic feedback to prescribers.

This community service program addressed the limited capacity of educators to use artificial intelligence in a structured and pedagogically responsible way for textbook development. The program focused on empowering educators through NotebookLM in the Ngabuburit AI 2026 activity. Its objective was to improve participants’ understanding and practical skills in organizing sources, designing textbook structures, developing chapter content, and generating interactive learning media. The program used a participatory training approach consisting of presentation, demonstration, guided practice, discussion, and feedback-based evaluation. The results showed that participants gained a clearer understanding of AI-assisted academic writing workflows and recognized NotebookLM as a useful tool for integrating source analysis, textbook writing, and learning media preparation. The activity also fostered new awareness that artificial intelligence can strengthen, rather than replace, educators’ academic roles in producing more systematic and interactive teaching materials.

SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 byToni Firmansyah, S. Farm., Apt. and Asrianty Salam, Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

This research is motivated by the need for interactive digital learning media to increase interest in learning and understanding of multiplication concepts in elementary school students. This study aims to develop interactive Math Space media based on space math adventure games on multiplication material for third-grade students of Mursyidah Elementary School and assess its feasibility based on aspects of validity, response, and effectiveness. The method used is research and development with a 4D model that includes the stages of definition, design, development, and dissemination. Data were collected through expert validation, teacher and student response questionnaires, and learning outcome tests. The results showed that the Math Space media has a very high level of validity with a percentage of 94% from material experts and 95% from media experts. Meanwhile, positive responses from teachers and students were 94.5% which is included in the very good category. Meanwhile, the effectiveness test produced an N-gain value of 0.87 which is in the very effective category, so this media is proven to be able to significantly improve understanding of multiplication concepts. Based on these results, it can be concluded that the interactive Math Space media is valid, has received positive feedback, and is effective for use in learning mathematics, especially multiplication, and has the potential to be developed for other materials and subjects.

This study aims to examine the implementation of Continuous Improvement (CI) within the Plan–Do–Check–Act (PDCA) framework at the village government level, focusing on governance, community engagement, and livelihood sustainability. The study employed a qualitative approach with an interpretive case study strategy, through document review and in-depth interviews. The results indicate that CI practices at the village level are contextual and adaptive, and most closely align with the incremental (Kaizen) approach that emphasizes incremental improvement, community participation, and continuous learning. The PDCA cycle serves as a reflective mechanism that allows village governments and communities to adjust policies and programs based on empirical evaluation and social feedback. Theoretically, these findings extend the study of CI in the local public sector by emphasizing its relevance to village governance. Practically, this study demonstrates that strengthening documentation, data-driven evaluation, and human resource capacity are key to CI sustainability at the village level.

Background: Digital transformation in arts education has introduced new paradigms in pedagogical tools, yet the specific role of artificial intelligence in fostering creativity within dance education remains under-explored. Objective: This study aims to analyze the contribution of AI Motion technology to enhancing the creative thinking skills of junior high school students in dance learning. Method: A systematic literature review was conducted following the PRISMA 2020 guidelines. A total of 30 peer-reviewed articles published between 2023 and 2025 were selected from databases including Scopus, ScienceDirect, ERIC, Google Scholar, and Garuda. Data were analyzed using the qualitative descriptive framework of Miles and Huberman. Results: The findings demonstrate that AI Motion technology significantly improves movement accuracy by up to 41% and fosters four key dimensions of creativity: fluency, flexibility, originality, and elaboration. The technology provides real-time feedback and visualization, enabling students to transition from passive imitation to autonomous movement exploration. Conclusion: The integration of AI Motion is strategically aligned with the Indonesian Merdeka Curriculum, which emphasizes differentiated learning and 21st-century skills. However, successful implementation is contingent upon overcoming challenges related to teacher digital competency and infrastructure accessibility. This study provides a conceptual framework for modernizing arts pedagogy through AI-assisted creative exploration.

Social media has evolved into a significant platform where consumers freely express their opinions, experiences, and levels of satisfaction regarding various products, including those offered by Micro, Small, and Medium Enterprises (MSMEs). The comments and reviews shared by customers on these platforms contain diverse sentiments that can serve as valuable indicators of how consumers perceive product quality. Understanding these sentiments is crucial for MSME owners, as it allows them to evaluate their products and adapt to market expectations more effectively. This study aims to analyze customer sentiment toward MSME products on social media by utilizing the Naïve Bayes algorithm, a widely used classification method in text mining. The data used in this research consist of customer comments collected from various social media platforms. The research process involves several stages, including data collection, manual labeling of sentiments, text preprocessing (such as tokenization, case folding, and stopword removal), and splitting the dataset into training and testing subsets. Subsequently, the classification process is carried out using the Naïve Bayes algorithm to categorize sentiments into positive, negative, and neutral classes. The results of this study demonstrate that the Naïve Bayes method is effective in classifying customer sentiments with a satisfactory level of accuracy. These findings provide a comprehensive overview of consumer perceptions regarding the quality of MSME products. Furthermore, this research is expected to assist MSME business owners in understanding customer feedback more systematically and using it as a basis for improving product quality and enhancing customer satisfaction in a competitive digital marketplace.

This study aims to analyze the implementation of group guidance services in developing alpha girl characteristics among senior high school (SMA) female students. The method used is a literature review by examining various relevant sources, including books and scientific journals published within the last five years. The findings indicate that group guidance plays a significant role in shaping alpha girl characteristics through social interaction, group dynamics, communication skills, and participatory learning experiences. Through the stages of formation, transition, core activities, and termination, students gradually experience improvements in self-confidence, independence, leadership ability, and the courage to express themselves in social settings. This developmental process does not occur instantly but emerges through repeated experiences supported by a conducive group environment, effective facilitation from counselors, and continuous self-reflection. In addition, peer feedback within the group contributes to strengthening personal awareness and emotional maturity. Therefore, group guidance services can serve as an effective and systematic strategy in supporting the development of alpha girl characteristics among senior high school female students.

This study aims to examine the application of artificial intelligence (AI) in learning to write scientific papers and its impact on the level of originality of students in the Indonesian Language and Literature Education Study Program (PBSI) Semester VI at Bina Bangsa University. This study uses a qualitative method with a descriptive approach, which was conducted through reference searches and interviews with 30 of the total 35 students. The results of the study indicate that AI is utilized functionally as an aid in the writing process, such as compiling outlines, paraphrasing, developing ideas, and reviewing writing. Based on the interview results, the use of AI platforms is dominated by Chat GPT at 50%, followed by Perplexity at 27%, and Gemini.ai at 23%. These findings indicate that students do not rely on a single platform, but rather utilize various technologies adaptively according to their needs. In terms of discussion, the use of AI has a positive impact in the form of improved writing quality, time efficiency, development of creative ideas, increased digital literacy, and the provision of instant feedback. However, there are also challenges that arise, such as the potential for decreased originality, dependence on AI, the risk of violating academic ethics, information bias, and data privacy issues. Therefore, AI should be used as a tool, not a substitute for students' critical thinking skills. This research emphasizes the importance of using AI wisely, critically, and responsibly so that students can produce original, high-quality, and integrated scientific work in the digital age.

The use of AI in today’s era has significantly expanded across various sectors of life, including the education sector. The use of AI in education is quite helpful in improving the quality of learning by providing innovative teaching materials, real-time feedback, and fostering student creativity; however, in practice, there are numerous instances of misuse of AI, such as for criminal activities. Such practices are clearly counterproductive to the learning process and threaten the quality of the nation’s future generations. The objective of this community service initiative is to deepen students’ understanding of AI from a legal perspective and to enhance the quality of learning. The methods employed include participatory-based education, encompassing lectures, Q&A sessions, and statements of commitment. The results of this community service initiative include an enhanced understanding of AI and its proper use. Additionally, students have committed to using AI ethically, in accordance with existing legal frameworks, and with a focus on improving the quality of learning without compromising their foundational and social skills, so that in the future they can compete effectively both nationally and internationally.

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 rapid proliferation of learning analytics, business intelligence (BI), artificial intelligence (AI), and generative AI (GenAI) has significantly expanded universities’ ability to collect, integrate, analyze, and operationalize institutional data. However, despite advances in predictive analytics, dashboards, and AI-driven systems, the translation of analytical outputs into consistent and accountable institutional decision-making remains uneven. This systematic literature review synthesizes contemporary research on analytics-enabled decision-making in higher education with the aim of moving beyond dashboard-centric perspectives toward a socio-technical and computing-oriented understanding of how data are transformed into institutional actions and outcomes. Guided by the PRISMA framework, the review synthesizes evidence across four interconnected dimensions: data ecosystems and learning analytics foundations; analytics capability, BI adoption, and digital readiness; AI and advanced analytics for decision support; and human-in-the-loop (HITL) decision routines and institutional outcomes. The findings show that predictive performance and analytical sophistication alone do not guarantee decision value. Instead, effective analytics-enabled decision-making depends on interoperable data ecosystems, organizational analytics capability, governance mechanisms, explainability, and sustained human oversight. Based on these findings, this review contributes a computing-oriented decision-intelligence framework that conceptualizes analytics-enabled decision-making as an end-to-end socio-technical pipeline linking heterogeneous data acquisition, integration, feature construction, analytical modeling, explainability, human validation, governance, and feedback-based refinement. By integrating learning analytics, BI, AI, GenAI, and HITL mechanisms within a unified framework, the review clarifies how universities can move beyond dashboard-based reporting toward accountable, adaptive, and institutionally actionable decision-support infrastructures.

The development of digital technology provides new opportunities for learning innovation, including in literature learning at Sma Negeri 1 Serang City. This study aims to describe the use of Blogger as a literature learning medium in improving short story writing skills of high school students in the digital era. This study uses a qualitative approach with descriptive methods. The subjects of the study were students of SMA Negeri 1 Serang City with a population of approximately 1,756 students who participated in short story writing learning based on Blogger as a publication and learning medium. Data collection techniques were carried out through observation, interviews, and document analysis of the results of students' short stories published on Blogger. The purpose of this study is to determine the benefits of using Blogger in literature learning to increase student learning motivation, provide space for creativity in writing, and make it easier for students to publish and share their literary works digitally. In addition, Blogger media also encourages students to be more active in the learning process because of interactions through comments and feedback from teachers and peers. Thus, the use of Blogger as a literature learning medium can be an innovative alternative in improving short story writing skills of high school students in the digital era.

The exponential growth of digital music catalogs on streaming platforms such as Spotify has made personalized recommendation systems crucial for enhancing user experience. This study develops a hybrid music recommendation system that addresses both warm-user and cold-user scenarios by combining Alternating Least Squares (ALS) collaborative filtering with content-based filtering (CBF) augmented by a popularity component. The dataset consists of 8,549,544 user-track interactions and a master file of 1,204,025 tracks with ten audio features. After preprocessing, users were segmented into 14,880 warm users and 723 cold users based on a five-interaction threshold. The ALS model was trained on the user-item implicit feedback matrix and tuned through grid search over factors, alpha, and regularization. CBF was implemented using cosine similarity on normalized audio features, while popularity scores were applied for new users with insufficient history. Evaluation used Precision@10, Recall@10, and NDCG@10. The final ALS configuration achieved NDCG@10 of 0.1116, representing a 30% improvement over baseline, while the hybrid CBF improved NDCG@10 for cold users from 0.0070 to 0.0201. Findings indicate that adaptive routing among ALS, CBF, and popularity reliably handles different user states, providing a practical foundation for production-grade music recommendation systems.

Stroke often causes hemiparesis, which impairs hand motor skills and independence in daily activities. Mirror therapy is a rehabilitation intervention that stimulates motor function through visual feedback, while patient motivation plays a crucial role in exercise adherence. This study aims to analyze the effect of mirror therapy and patient motivation on hand motor skills in patients with hemiparesis.The study used a quasi-experimental design with a pretest–posttest approach in 30 hemiparesis patients undergoing rehabilitation at the Ciherang Community Health Center. Mirror therapy intervention was administered for 20–30 minutes, three times per week for four weeks. Hand motor skills were measured using Manual Muscle Testing on a scale of 0–5, while patient motivation was assessed using a questionnaire.The results showed a significant increase in hand motor skills after mirror therapy (p < 0.05) and higher patient motivation was associated with greater motor score improvement (p < 0.05). Mirror therapy and patient motivation have been shown to have a positive effect on hand motor skills in hemiparesis patients, so this combined intervention can be considered as part of a stroke rehabilitation program.

Science learning in elementary schools requires evaluation strategies that are able to measure conceptual understanding while enhancing students’ motivation and engagement. One of the contextual science topics in Grade VI that requires visualization is the adaptation of living organisms. However, science learning evaluation is still dominated by conventional assessment instruments that are less varied and have not optimally utilized digital technology. This study aims to examine the development of an interactive question bank based on Quizlet as an alternative assessment tool for science learning on the topic of adaptation of living organisms in Grade VI elementary schools. This study employs a qualitative approach using a literature review method by analyzing relevant scientific articles, books, and educational policy documents. The results of the review indicate that a Quizlet-based interactive question bank has the potential to improve the quality of learning evaluation through the use of varied and interactive questions accompanied by immediate feedback. The use of Quizlet also supports student-centered learning and aligns with the principles of meaningful assessment promoted in the Merdeka Curriculum.

This literature study examines the process of self-regulation in transforming compliance with school rules originating from external pressure into behavioral regularity emerging from personal awareness, and its impact on the effectiveness of student learning outcomes. Using a qualitative approach with content analysis method, this study synthesizes relevant literature to build a theoretical framework on how self-regulation facilitates the internalization of disciplinary values. The findings reveal that self-regulation occurs through a series of interconnected stages including goal setting, strategy planning, self-monitoring, evaluation, and adjustment. The success of this process is determined by internal motivation, appropriate environmental support, positive direct experiences, and healthy emotional management. Strong self-regulation directly impacts learning outcome effectiveness through improved cognitive strategies, strengthened intrinsic motivation, enhanced time and environment management, and developed capacity to constructively cope with failure. Learning outcomes achieved through self-regulation processes are characterized by lasting understanding, knowledge transfer ability, and the formation of lifelong learning dispositions. Schools and teachers play strategic roles in strengthening self-regulation through curriculum design that supports autonomy, formative feedback, role modeling, and collaboration with parents. This study contributes theoretically by positioning self-regulation as the central mechanism bridging external influences and internal disposition formation.