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Supplier selection is a strategic aspect of supply chain management that directly impacts product quality and operational efficiency within a company. PT. XYZ, operating in the fashion industry, is currently facing the challenge of selecting the optimal t-shirt supplier and lacks an appropriate decision-making method. The objective of this research is to provide insights into the best decision-making approach for PT. XYZ by applying the Analytical Hierarchy Process (AHP) method. The determination of suppliers is carried out by considering four main criteria, namely product quality, product price, delivery time, and service. The data obtained were generated from interviews and questionnaires given to the owner of PT. XYZ. The results of the analysis have shown that product quality is the most influential criterion with a weight of 0.716, followed by service (0.113), delivery time (0.093), and product price (0.078). The final result states that supplier C has the highest priority weight, which is 0.763. Therefore, PT. XYZ is recommended to choose supplier C as the best alternative supplier. The results of this study indicate that the AHP method can be used as a systematic and objective decision-making tool for supplier selection.

This article examines the spiritual needs of Christian youth and identifies effective ministry strategies for supporting their faith formation. The study explores how child ministry foundations contribute to developing spiritual maturity during adolescence, a phase marked by rapid emotional and social changes. Using a descriptive approach, the discussion highlights core spiritual needs such as identity in Christ, meaningful discipleship, and supportive mentoring environments. The findings suggest that intentional ministry strategies such as relational mentoring, contextualized teaching, and participatory faith practices play a significant role in strengthening the faith and character of young believers. The article concludes that churches and educators must design holistic, youth-centered ministry programs that respond to contemporary challenges while nurturing long-term spiritual growth.

Gestational Diabetes Mellitus (GDM) is a pregnancy-related metabolic disorder that poses health risks to both mother and fetus if not detected early, requiring accurate prediction methods for early screening and clinical decision-making. This study applies the Random Forest algorithm to detect GDM risk using clinical data from the Pima Indian Dataset. Data preprocessing included handling missing values, standardization, feature engineering, and a 70:30 train–test split. Two models were developed: a baseline and an optimized model using GridSearchCV hyperparameter tuning, validated with 5-fold cross-validation. Performance was assessed using a classification report, confusion matrix, and ROC–AUC. Results show that the optimized model outperforms the baseline, achieving 88% accuracy, an AUC of  93%, and average recall of 81%–85%. Compared to previous studies, this approach demonstrates improved predictive performance. The findings indicate that combining Random Forest with comprehensive preprocessing, feature engineering, and model optimization is effective and feasible for developing a medical decision support system for early GDM risk screening.

This study aims to examine the effect of employee competence, behavioral control, and trust on employee performance at the Bojonegoro District Health Office with Organizational Citizenship Behavior (OCB) as an intervening variable. The background of this study is related to the importance of employee performance in achieving public service organizational goals, particularly in the health sector. This study uses an explanatory quantitative method with a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The research sample consisted of 100 employees at the Bojonegoro District Health Office. The results of the analysis show that the influence of employee competence on employee performance is not significant, but employee competence has a significant influence on OCB. Behavioral control has a significant effect on employee performance, but its effect on OCB is not significant. Trust has a significant effect on OCB, but its direct effect on employee performance does not. OCB is proven to have a significant effect on employee performance. Therefore, OCB plays an important role as a mediator in improving employee performance. This study provides a theoretical contribution by clarifying the relationship between variables in the context of public service-based government organizations. In practical terms, the results of this study are expected to form the basis for recommendations to improve the quality of human resources and develop managerial strategies at the Bojonegoro District Health Office in order to support the effectiveness and efficiency of public services.

The implementation of the eighth-grade Christian Religious Education teaching module on the topic "Love as the Foundation of a Believer's Life" was carried out as an effort to provide an active, reflective, and contextual learning process in accordance with the principles of the Independent Curriculum. Learning is designed through an interactive approach with discussion activities, analysis of biblical texts, case studies, problem-solving, and personal reflection that provide opportunities for students to construct understanding independently. Through these activities, students are guided to understand the concept of agape love as sincere love, giving without expecting anything in return, and is manifested in concrete actions towards others. The implementation results show that this teaching module is able to improve students' conceptual understanding of the meaning of love from a biblical perspective and its relevance in modern life. Students appear to be increasingly confident in expressing opinions, are able to work together in groups, and are actively involved in learning activities. In addition, the emergence of attitudes of empathy, tolerance, and habits of helping each other are indicators that the value of love is not only understood cognitively, but also internalized in behavior. This teaching module also contributes to improving students' critical thinking skills and spirituality through reflection activities that invite them to evaluate acts of love in daily life at school, family, and society.

This study aims to implement the Christian Religious Education and Character Education (PAK) teaching module in grade V of SDN 1 Sabaru, Palangka Raya, with a focus on the topic “Jesus Was Crucified, Died, and Risen for Me.” The learning process is designed to support students’ spiritual and character development through an interactive and project-based approach. Teaching methods include group discussions, the use of miniature media as visual learning aids, collaborative activities, and guided reflection on Christian values relevant to students’ daily experiences. The results of classroom observations show that most students are active, enthusiastic, and involved in the learning process, able to understand the theological meaning of the crucifixion, death, and resurrection of Jesus, and apply the values of love, gratitude, and responsibility in everyday life. Obstacles found include a lack of self-confidence in some students and less optimal group dynamics during activities. These findings serve as important evaluation materials for improving the effectiveness of future learning implementation

This study aims to analyze the effectiveness of technical personnel management in handling main engine failures during extreme weather conditions at sea. The main focus of this study is to assess the extent to which technical competence, communication, coordination, and preparedness of technical personnel contribute to the effectiveness of damage management. The method used is a descriptive quantitative approach with data collection through a closed-ended questionnaire based on a Likert scale. A total of 100 respondents who are ship engineering officers currently studying at a maritime campus were sampled. The results of the analysis show that the four independent variables (technical competence, communication, coordination, and preparedness) simultaneously have a significant effect on the effectiveness of handling main engine failures. From the results of the multiple linear regression test, the coefficient of determination (R²) value of 0.897 indicates that 89.7% of the variation in damage management effectiveness can be explained by these four variables. This finding indicates that good technical personnel management plays a significant role in reducing the risk of engine system failure during extreme weather.

This study aims to analyze the influence of Innovative Work Behaviour, Upskilling, and Work Ethic on the Health Workers Performance with Intention to Stay as an intervening variable at RSUD Sumberrejo. The background of this research stems from challenges in improving service quality, high workload, and the need to strengthen competency and retention among health workers. The study employs a quantitative approach using a survey method through the distribution of questionnaires, with data analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) through SmartPLS version 4.0. The population consists of 216 employees, and the sampling technique used is non-probability sampling, resulting in 140 respondents. The findings reveal that Innovative Work Behaviour, Work Ethic, and Intention to Stay have a significant positive effect on the performance of health workers. In addition, Innovative Work Behaviour and Work Ethic significantly influence Intention to Stay. However, Upskilling shows a positive but non-significant effect on both Intention to Stay and Performance, indicating that skill enhancement requires managerial support and motivation to contribute effectively to employee performance. Intention to Stay serves as a mediating variable in several relationships among the constructs. Strengthening innovative behaviour, work ethic, and competency development, accompanied by appropriate retention strategies, is essential for improving the performance of health workers in regional hospitals. Future studies are recommended to develop the research model by incorporating additional variables that may have stronger effects on Intention to Stay and Performance.

This study is motivated by the high frequency and significant impacts of flooding in Indonesia, particularly the recurrent flooding of the Kali Lamong River in Gresik Regency, which causes substantial socio-economic losses each year. Although disaster management is normatively regulated by national policies, its effectiveness depends largely on collaborative governance among multiple actors. This study aims to analyze the practice of collaborative governance in flood mitigation in Gresik Regency using the model of Weber, Lovrich, and Gaffney (2005), which includes vertical, horizontal, and partnership dimensions, and to identify the key challenges that hinder its implementation. A descriptive qualitative approach was employed in flood-affected areas along the Kali Lamong River, involving BPBD, DPUTR, sub-district governments, village authorities, and local communities through interviews, observations, and document analysis. The findings reveal that collaboration has been established and functions relatively well, particularly in hierarchical coordination, division of roles among government agencies, strengthening of Destana, KENCANA, and SPAB programs, as well as CSR involvement and community participation all contributing to reduced flood duration. However, the implementation of collaborative governance remains constrained by slow land acquisition and infrastructure development, a predominantly reactive orientation, suboptimal early-warning systems between upstream and downstream areas, and uneven support from the private sector and academia. The study concludes that strengthening collaborative mechanisms and accelerating the resolution of structural barriers are essential to achieve more sustainable flood mitigation efforts in Gresik.

People with disabilities, especially the blind, still face various structural and cultural barriers that impact their psychological well-being and ability to participate in social life. Resilience is an important aspect that enables blind individuals to recover from pressure, stigma, and environmental limitations. This study aims to understand the role of the Sahabat Mata Community in shaping the resilience of its members. This study is a qualitative study using a phenomenological approach involving three subjects, namely members and administrators of the Sahabat Mata Community (KSM). Data collection methods were carried out through semi-structured interviews, participant observation, and document studies. The results of the study indicate that the Sahabat Mata Community (KSM) has contributed to the resilience of its members based on seven aspects of resilience according to Reivich & Shatte including emotional regulation, impulse control, optimism, problem-analyzing ability, self-efficacy, empathy, and achievement. The formation of resilience is strengthened through social processes, emotional support and opportunities to achieve self-potential formed in the Sahabat Mata Community. The findings of this study reveal that the Sahabat Mata Community as an inclusive community plays a role as a safe space for the formation of resilience of people with disabilities.

The development of digital technology has brought about significant changes in the way society constructs identity and interprets culture. This study aims to examine how cultural literacy and social media use influence each other in the process of cultural transformation in Indonesia. The research was conducted using a qualitative descriptive approach through a review of various relevant literature sources. The results indicate that the flood of unfiltered digital information often leads to misunderstandings, shifts in cultural values, and the weakening of local identity. On the other hand, social media continues to provide significant opportunities to preserve traditions and promote local culture through various forms of digital content. This study also found that digital literacy including the ability to think critically, understand visual context, and assess the credibility of information is key to society's wise use of social media. The younger generation plays a crucial role in this process as they are the largest users of social media and the primary producers of cultural content. The synergy between cultural literacy, digital literacy, and responsible use of social media plays a role in guiding the nation's cultural transformation in a more positive direction.

: The rapid expansion of cybersecurity standards and threat intelligence frameworks has led to significant semantic fragmentation among security terminologies, hindering effective information retrieval and interoperability across systems. Traditional keyword-based search approaches are inadequate for capturing the contextual meaning of security terms, particularly within formal frameworks such as NIST, MITRE ATT&CK, and CWE. This study addresses this challenge by proposing CyberBERT, a transformer-based semantic search framework designed to align cybersecurity terminologies through deep contextual representation and ontology-driven reasoning. Research Objectives: The primary objective of this research is to develop a semantic retrieval model capable of understanding conceptual relationships between security terms beyond lexical similarity. Methodology: The proposed methodology fine-tunes a BERT-based model on the NIST Glossary corpus using a combination of masked language modeling and triplet loss objectives to generate discriminative semantic embeddings. These embeddings are further aligned with cybersecurity ontologies, including MITRE ATT&CK and CWE, to enhance semantic consistency and explainability. Semantic retrieval is performed using cosine similarity within a 768-dimensional embedding space and evaluated using Mean Reciprocal Rank (MRR) and Precision@K metrics. Results: Experimental results demonstrate that CyberBERT achieves an MRR of 0.832, outperforming domain-adapted baselines such as SecureBERT and CyBERT. The integration of ontology alignment improves semantic accuracy by over 6%, while robustness evaluations confirm resilience against adversarial linguistic perturbations. Visualization using t-SNE reveals coherent semantic clustering aligned with the five core NIST Cybersecurity Framework functions. Conclusions: In conclusion, CyberBERT effectively bridges semantic gaps across cybersecurity terminologies by combining transformer-based contextual learning with ontological reasoning. The framework offers a robust, interpretable, and scalable solution for semantic search, supporting improved interoperability and knowledge discovery in cybersecurity operations and standards harmonization.

Abstract: The rapid diffusion of Generative Artificial Intelligence (AI) has intensified public debate regarding its benefits, risks, and societal implications. This study investigates public sentiment and thematic structures surrounding Generative AI by analyzing Twitter discourse as a representation of large-scale, real-time public perception. The research addresses two main problems: how public sentiment toward Generative AI is distributed and what dominant themes shape this perception. Accordingly, the objective is to map both emotional polarity and thematic narratives embedded in social media conversations. A computational mixed-methods approach was employed using a dataset of 12,470 tweets collected on 17 December 2024. Sentiment classification was conducted using a transformer-based DistilBERT model, while semantic representations were generated with Sentence-BERT. Topic modeling was performed using BERTopic, integrating HDBSCAN clustering and class-based TF-IDF to extract coherent and interpretable topics. Human-in-the-loop validation supported the interpretive robustness of topic labeling. The findings reveal that public sentiment toward Generative AI is predominantly positive (41.8%), particularly in relation to productivity enhancement, education, and creative applications. Neutral sentiment (31.4%) reflects informational discourse, while negative sentiment (26.8%) centers on ethical concerns, privacy risks, misinformation, and AI hallucinations. Seven dominant topics were identified, with clear topic–sentiment alignment showing optimism in utility-driven themes and skepticism in ethics- and risk-related discussions. In conclusion, public perception of Generative AI is dualistic—characterized by strong enthusiasm alongside persistent caution. These results provide empirical insights for AI governance, responsible innovation, and future research on socio-technical impacts of Generative AI. *    

End-to-end autonomous driving has emerged as a promising paradigm in which deep neural networks directly map raw visual inputs to continuous control actions. Despite its effectiveness, this approach suffers from limited transparency, posing significant challenges for deployment in safety-critical driving scenarios. This study addresses the lack of interpretability in vision-based end-to-end autonomous driving systems and aims to analyze model decision-making behavior under critical conditions such as sharp steering maneuvers and abrupt control transitions. To this end, an explainable end-to-end autonomous driving framework is proposed, combining a convolutional neural network trained via imitation learning with gradient-based visual attribution techniques, including Grad-CAM. The model predicts continuous steering, throttle, and braking commands directly from front-facing camera images, while explainability mechanisms are applied to reveal input regions influencing each control decision. Model performance is evaluated using both prediction accuracy and safety-oriented behavioral metrics. Experimental results show that the proposed explainable model achieves lower control prediction errors compared to a baseline end-to-end CNN, reducing steering mean squared error from 0.034 to 0.031, throttle error from 0.021 to 0.019, and brake error from 0.018 to 0.016. Moreover, safety-oriented analysis indicates improved driving stability, with steering variance reduced from 0.087 to 0.072 and abrupt control changes decreased from 14.6 to 10.3 events. Visual explanations consistently highlight road surfaces and lane-related structures during complex maneuvers, indicating reliance on semantically meaningful cues. In conclusion, the results demonstrate that integrating explainability into end-to-end autonomous driving not only preserves predictive performance but also correlates with smoother and more stable driving behavior. This framework contributes to the development of transparent and trustworthy autonomous driving systems suitable for safety-critical applications

Recommender systems play a critical role in shaping user decisions across digital platforms; however, the increasing complexity of recommendation algorithms has raised serious concerns regarding transparency, trust, and accountability. This study focuses on enhancing the transparency of recommender systems by integrating Explainable Artificial Intelligence (XAI) techniques within a MovieLens-based recommendation framework. The primary problem addressed is the opacity of conventional recommendation models, which limits user understanding of why certain items are recommended and may reduce trust, perceived fairness, and system acceptance. Accordingly, the main objective of this research is to design and evaluate a hybrid explainable recommender system that balances predictive accuracy with human-understandable explanations. The proposed approach combines Matrix Factorization, feature-importance-aware neural networks, and knowledge graph embeddings to construct a robust recommendation model. To enhance explainability, multiple XAI strategies are integrated, including model-agnostic methods (LIME, SHAP, and CLIME), argumentation-based explanations, and context-aware personalized explanations. A comprehensive evaluation framework is employed, incorporating algorithmic metrics (accuracy, fidelity, robustness, counterfactual consistency, and fairness) alongside human-centered evaluations measuring trust, transparency, cognitive load, and perceived usefulness. Experimental results demonstrate that the knowledge graph–enhanced hybrid model achieves superior recommendation accuracy compared to baseline approaches. Moreover, context-aware explanations consistently outperform other methods in terms of fidelity, robustness, and user-perceived transparency, while argumentation-based explanations are found to be the most persuasive. CLIME offers a strong balance between technical stability and interpretability. The findings indicate that no single explainability technique is universally optimal; instead, hybrid and adaptive explanation strategies are most effective. In conclusion, this study confirms that human-centered, context-adaptive XAI significantly improves transparency and user trust in recommender systems, highlighting explainability as a fundamental component rather than an optional enhancement.

Anxiety is an excessive state of tension characterized by feelings due to a response to stress or conflicting conditions. This study aims to investigate the relationship between anxiety disorders and sleep quality among nursing students during the Objective Structured Clinical Examination (OSCE) in the Diploma III Nursing Program, Faculty of Health Sciences, Abulyatama University. This study consisted of 168 individuals. The sample was 65 respondents selected using a purposive sampling technique. The research was conducted from July 25th to 29th, 2025. This study employed a descriptive analytical method with a cross-sectional approach. The research instruments were the Zung Self-Rating Anxiety Scale (ZSAS) and the Pittsburgh Sleep Quality Index (PSQI). The data was analyzed using the Chi-Square test. The research results indicated a significant relationship between anxiety disorders and the sleep quality of students during the OSCE at the Diploma III Nursing Program, Abulyatama University, with a p-value of 0.025 (p < 0.05). Based on this finding, this study proves a relationship between anxiety disorders and sleep quality among the Diploma III students during the OSCE preparation. This study suggests that students and the university provide counselling sessions before the test to reduce the effects of anxiety disorders in students. Therefore, this study serves as a resource to raise awareness on how to manage emotions during exam preparation.

This study aims to explore the philosophy of Islamic education grounded in tolerance by revisiting the influential ideas of Gus Dur and assessing their significance for the younger generation in contemporary society. Adopting a qualitative descriptive approach through document analysis, in-depth interviews, and thematic interpretation, the research highlights that values such as tolerance, humanism, intellectual freedom, and respect for diversity are essential foundations for shaping modern Islamic education. The findings indicate that incorporating these principles into educational curricula not only enriches the learning experience but also strengthens inclusive and participatory teaching practices, fostering an environment that encourages open dialogue, mutual understanding, and moderation. Furthermore, the study emphasizes that systematic integration of Gus Dur’s educational philosophy can contribute to the development of students’ critical thinking, ethical awareness, and social responsibility, ensuring that Islamic education remains relevant and responsive to contemporary societal challenges. Overall, the research concludes that implementing these values consistently is crucial for advancing a modern, tolerant, and pluralistic approach to Islamic education that benefits both individuals and society as a whole.

This study aims to determine the relationship between learning motivation and learning outcomes in SMAW welding engineering among eleventh-grade students at SMKN 2 Solok. This research employed a quantitative method with a correlational approach. The population consisted of all students from classes XI TPM 1 and XI TPM 2, totaling 51 students, using a total sampling technique. Learning motivation data were collected through a validated and reliable questionnaire, while learning outcome data were obtained from post-test scores in the SMAW welding subject. Data were analyzed using the Pearson Product Moment correlation test with the assistance of SPSS software. The results showed a correlation coefficient of r = 0.783 with a significance value of 0.000 < 0.01, indicating a strong, positive, and statistically significant relationship between learning motivation and students’ learning outcomes. These findings suggest that higher learning motivation leads to better learning outcomes in SMAW welding engineering. Therefore, learning motivation plays an important role in improving students’ academic performance. This study is expected to provide useful insights for teachers and schools in developing instructional strategies that enhance students’ motivation and learning outcomes.

The mathematics learning outcomes of students at SMP Negeri 3 Bontang on Rational Numbers are still relatively low. Data from the 2019 National Examination (UN) shows an average math score of 46.43, which is in the "poor" category. Summative assessment results indicate that most students have not yet achieved the Learning Objective Achievement Criteria (KKTP). This situation indicates that the learning process tends to be conventional and lacks active student engagement. Therefore, a more innovative learning model is needed, one of which is the Team Games Tournament (TGT), which combines group work, competition, and educational games. This study aims to determine the effect of the TGT learning model on the mathematics learning outcomes of seventh-grade students at SMP Negeri 3 Bontang in the topic of Rational Numbers. This study used a quantitative approach with a quasi-experimental type and a Posttest-Only Control Group Design. The study population was 203 seventh-grade students in the 2024/2025 academic year, with a sample consisting of class VII A as the experimental group (33 students) and class VII F as the control group (34 students), selected through a purposive sampling technique. The research instrument was a five-item essay test. The analysis results showed that the average posttest of the experimental group was 67.848, higher than the control group at 61.794. The Independent Sample t-Test produced a significance value of 0.031 <0.05, so H₀ was rejected. This indicates that the Team Games Tournament (TGT) learning model has a significant effect on improving students' mathematics learning outcomes in the Rational Numbers material.

Physical fitness is a fundamental determinant of athletic performance and is strongly influenced by dietary intake and lifestyle behaviors. Adequate protein consumption is essential for muscle development and energy metabolism, whereas smoking has detrimental effects on lung function and aerobic capacity. This study aimed to explore the relationship between protein intake and smoking habits with physical fitness, measured by maximal oxygen uptake, among athletes of Persela Football Academy under-eighteen. A quantitative approach with a cross-sectional design was applied, involving adolescent male athletes. Protein intake was assessed using a semi-quantitative food frequency questionnaire, smoking habits were obtained through structured interviews, and maximal oxygen uptake was measured using the multistage fitness test. Findings revealed that the average daily protein intake of athletes was relatively high, while the mean maximal oxygen uptake score fell within the good category. Correlation analysis demonstrated a significant association between protein intake and aerobic fitness, as well as between smoking habits and aerobic fitness. The results indicate that lower protein intake and higher smoking frequency are linked to reduced physical fitness capacity. This study highlights the importance of nutritional interventions and healthy lifestyle promotion as integral components in the development of youth athletes to optimize performance and prevent decline in fitness.