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This study aims to provide a comprehensive analysis of Predictive Policing and its implications for law enforcement transformation in Indonesia, based on an extensive review of its global applications, benefits, and challenges. The study uses qualitative literature and international case study review methods to assess the impact and complexity of implementing digital technologies such as artificial intelligence (AI), machine learning, and big data analytics within a Predictive Policing framework. The results of this review highlight that while Predictive Policing offers significant potential for proactive crime prevention and increased operational efficiency, its implementation is consistently fraught with critical legal, ethical, and technical challenges, including regulatory gaps, risks of algorithmic bias, and data privacy concerns, which are particularly relevant to Indonesia. The findings underscore that public trust and police legitimacy in the context of adopting such technologies are strongly influenced by transparency, strong accountability mechanisms, and community involvement in shaping their use. This study contributes to the growing discourse on digital policing in developing countries and culminates in practical policy recommendations designed to guide the Indonesian police towards the development and implementation of Predictive Policing models that are effective, efficient, and fundamentally respectful of legal and human rights principles.

Tafsir tarbawi is an approach to interpreting the Qur’an that emphasizes the extraction of educational values to shape holistic human character. This study aims to analyze the implementation of tafsir tarbawi in the process of Islamic education and examine its relevance in shaping students’ character in the modern era. The research employs a qualitative method with a library research approach, where data are collected through the analysis of various academic sources such as books, scholarly journal articles, and relevant previous studies. The findings indicate that tafsir tarbawi can be effectively implemented through the integration of Qur’anic values into educational curricula, the application of value-based learning methods, and the reinforcement of teachers’ exemplary behavior as role models. Furthermore, this approach encourages the internalization of spiritual, moral, and social values within students. Therefore, tafsir tarbawi plays a strategic role in developing learners who are not only intellectually competent but also possess strong character, noble morals, and the ability to face life’s challenges wisely.

Tawhid education is a fundamental aspect of Islamic education that serves as the foundation for the formation of faith and individual religious character. The family plays a crucial role as the primary educational environment in instilling the values of Tawhid from an early age. However, in modern social realities, the role of families in Tawhid education often faces various challenges, necessitating support from non-formal Islamic educational institutions. This study aims to describe the role of families in Tawhid education through their involvement in the Majlis Taklim ‘Izzatin Nisa Tangerang. This study uses a qualitative approach with descriptive methods. Data collection techniques were carried out through observation, interviews, and documentation of the Majlis Taklim administrators, the congregation, and ongoing learning activities. The results show that families play an active role in Tawhid education through parental role models, the habit of worship at home, and the strengthening of understanding of the faith gained from the Majlis Taklim activities. The Majlis Taklim ‘Izzatin Nisa serves as an educational tool that strengthens the congregation's understanding of Tawhid and encourages its implementation in family life. Thus, the synergy between families and religious study groups has been proven to contribute to strengthening monotheism education and building religious awareness within the community.

The ability to analyze ethical and health law issues is one of the learning outcomes that must be mastered by students of the Public Health Study Program. Over the past two years, the implementation of lectures has been predominantly based on problem-based learning; however, most student learning outcomes have remained in the “not yet achieved” category, including in completing assignments related to ethical and health law problem solving. This study aims to compare students’ problem-solving abilities between the implementation of project-based learning and problem-based learning. The research was conducted in the Public Health Study Program at Universitas Jambi involving first-semester students enrolled in the Ethics and Health Law course. The research employed a quasi-experimental design involving 200 students, with 100 students assigned to the experimental group and 100 students to the control group. The instruments used were assessment sheets and observation sheets. Data collection was carried out twice, before and after the implementation of the two learning models. Data processing and analysis were conducted using an independent t-test.The results of the study indicate an improvement in students’ problem-solving abilities through the implementation of project-based learning. Project-based learning contributes to strengthening students’ perseverance and problem-solving skills and is therefore recommended for implementation in all courses at higher education institutions.

The policy to implement the deep learning approach in Indonesian schools starting from the 2025/2026 academic year requires teachers to be well prepared to design and conduct meaningful and in-depth learning. This community service program aimed to enhance the understanding and pedagogical competence of senior high school and madrasah economics teachers in Tasikmalaya City in implementing the deep learning approach comprehensively. The program employed a community-based science and technology application scheme through training and mentoring activities conducted in face-to-face, online, and hybrid modes, consisting of planning, implementation, and evaluation stages. The training materials covered the concept and implementation of deep learning, lesson planning, instructional design and models, learning evaluation, development of innovative technology-based learning media, and reinforcement of microeconomic and macroeconomic content. A total of 78 economics teachers participating in the MGMP of Tasikmalaya City were involved in the program. The results indicate that the training improved teachers’ understanding of deep learning, lesson planning, and assessment strategies that support meaningful learning. Participants’ reflections revealed high motivation and strong relevance of the training materials to their professional duties. This program contributes to strengthening teachers’ readiness to implement deep learning sustainably and supports the improvement of economics learning quality in schools.

This research is motivated by the use of conventional learning models that still dominate Indonesian language learning at the high school level, causing learning to become monotonous and less actively involving students. This study aims to determine the effectiveness of implementing the Quizizz-based Game Based Learning (GBL) model in improving learning outcomes, motivation, and participation of grade XII Social Science students at SMA BIMA Ambulu. The research method used is quantitative experimental with a one-group design (one-group pretest-posttest design). Research subjects consisted of 70 students divided into two classes, namely XII IPS 2 and XII IPS 5, with 35 students each. Data were collected through tests (pretest and posttest), learning motivation questionnaires using a 5-level Likert scale, student activity observation sheets, and documentation of learning activities. Research instruments have been tested for validity using Pearson Product Moment correlation and reliability using Cronbach's Alpha. Data analysis included validity tests, reliability tests, normality tests, and hypothesis testing using Independent Sample t-Test. The research results show that all test items are declared valid (r calculated > r table 0.334) and the instrument is reliable with a Cronbach's Alpha value of 0.812. The average N-Gain for class XII IPS 2 is 0.668 and class XII IPS 5 is 0.679, both in the medium-high category indicating the effectiveness of the GBL model. The t-test results show no significant difference between the two classes (mean difference 0.011), indicating consistency in the effectiveness of the GBL model in both groups. This study concludes that the Quizizz-based Game Based Learning model is proven effective in improving Indonesian language learning outcomes for grade XII Social Science students at SMA BIMA Ambulu. The implementation of GBL creates more interactive, enjoyable, healthy competitive learning, and is able to increase motivation and active student participation in learning.

Islamic Religious Education (PAI) learning has a strategic role in shaping the character of students who are religious, tolerant, and have noble morals. Amidst the reality of Indonesian multicultural society, PAI learning is required to be able to internalize the values of religious moderation as an effort to prevent extreme, radical, and intolerant attitudes. Religious moderation is an important paradigm in Islamic education to instill a balanced and contextual religious attitude. This proceedings article aims to examine the concept, strategy, and implications of moderation-based Islamic Religious Education learning through the Systematic Literature Review (SLR) approach. The SLR method is used to examine journal articles, scientific books, and proceedings relevant to the topic of PAI learning and religious moderation in the last ten years. The results of the study indicate that moderation-based PAI learning is based on the values of wasathiyah, tawazun, i'tidal, and tasamuh which are integrated into the curriculum, learning methods, and the role models of educators. The implementation of moderation-based PAI learning has a positive impact on the formation of inclusive, tolerant attitudes and the ability to live peacefully together in students. This article is expected to be an academic reference for educators and researchers in developing Islamic Religious Education learning that is relevant to the social challenges and diversity of Indonesian society.

Islamic education in the digital era faces significant challenges in improving the quality of learning and developing students' critical thinking skills. One promising solution is the implementation of deep learning-based Islamic education, which can facilitate the teaching of religious material more effectively and easily accessible via the internet. Deep learning has the potential to strengthen students' critical thinking skills and understanding of Islamic values ​​in a more interactive and personalized manner. This study used a literature review method to analyze various relevant literature sources. The results indicate that deep learning can increase student engagement, enable personalized learning, and provide real-time evaluation of learning progress. However, the implementation of this technology also faces challenges, particularly related to the availability and quality of relevant data. Therefore, efforts are needed to improve data quality and develop learning models tailored to student needs to achieve optimal results in technology-based Islamic education.

The integration of Augmented Reality (AR) technology into higher education has emerged as a promising approach to enhance collaborative learning experiences. This study aims to design and evaluate an AR multimedia framework that facilitates real time interaction and spatial visualization, creating immersive and engaging learning environments for students. The AR framework was developed with a focus on improving student engagement, collaboration, and learning outcomes through interactive 3D models and real time feedback. By leveraging AR technology, the study sought to address common challenges in traditional learning environments, such as limited student interaction and engagement, and lack of real time feedback. The experimental evaluation involved two student groups: one using the AR-based system and the other using conventional multimedia tools. Findings revealed that students using the AR framework showed significant improvements in engagement, interaction frequency, and collaborative task performance. Additionally, the AR framework contributed to better learning outcomes, including enhanced comprehension, retention of complex concepts, and improved problem-solving skills. The study also highlighted the importance of incorporating a user-centered design approach in developing AR applications to ensure that the system meets the needs and preferences of learners. Qualitative feedback from students indicated that the AR system provided an enriched learning experience, although challenges such as interface navigation were noted. Overall, the study demonstrates the effectiveness of AR in fostering collaborative learning and offers practical insights for its integration into higher education curricula. Future research should explore the integration of AR with other immersive technologies to further enhance collaborative learning experiences.

Teaching fiction in Indonesian language classrooms is often constrained by text-centered instruction and limited use of engaging digital media. In the era of Generation Z learners who are visually and digitally oriented, innovative learning materials are needed to enhance motivation, interpretation, and comprehension of literary texts. This study aims to develop and evaluate a Scribus-based digital magazine for fiction learning by integrating the ADDIE model within a qualitative descriptive framework. The research adopted a qualitative descriptive design comprising five stages of the ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. The study was conducted at SMP Negeri 10 Semarang, involving one Indonesian language teacher and fifteen Grade VIII students, who were selected through purposive sampling. Data were collected through observation, interviews, and documentation, and analyzed using the Miles and Huberman model (data reduction, data display, conclusion drawing). Media and content experts conducted validation to assess the feasibility, usability, and pedagogical quality of the content. Findings revealed that the Scribus-based learning media effectively increased students’ engagement and comprehension in analyzing fictional elements such as plot, character, and setting. Expert validation results indicated a high feasibility level, with mean scores above 85% in design and content quality. Teachers reported improved classroom interaction and creativity, while students expressed enthusiasm for the visual and interactive format. The study concludes that open-source tools, such as Scribus, can provide cost-effective and pedagogically sound alternatives for developing literary learning media. The integration of ADDIE and multimodal design promotes contextual, engaging, and sustainable learning experiences. Future research should explore multimedia enhancements, such as audio storytelling and cross-curricular applications, to broaden the pedagogical impact.

This study discusses the development of thematic teaching materials in elementary schools to improve the quality of learning in accordance with the 2013 Curriculum. The research method used is research and development with the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The results show that the thematic teaching materials developed with approaches such as Project Based Learning (PjBL), Problem Based Learning (PBL), and Contextual Teaching and Learning (CTL) can enhance students' critical thinking, creativity, and social responsibility skills. The integration of local wisdom values as well as the use of digital and contextual teaching materials make learning more engaging, interactive, and meaningful. The thematic teaching materials based on these innovative learning models can help students develop 21st-century skills. Thus, the development of thematic teaching materials based on innovative models is an effective strategy for creating quality learning in elementary schools that is relevant to curriculum demands and the needs of today's learners. The use of technology and contextual approaches enriches students' learning experiences, making them more relevant and beneficial in daily life.

In the learning process, educators often face challenges in helping students achieve optimal learning outcomes. One of the contributing factors is the dominance of teacher-centered learning models, which frequently leads to low student engagement and reduced motivation. This condition affects students’ curiosity, particularly in Science learning, which requires active participation and exploration. Therefore, innovative teaching materials are needed to encourage student involvement while simultaneously stimulating their curiosity. One alternative that can be utilized is the Student Worksheet (Lembar Kerja Peserta Didik/LKPD), which can be designed systematically and contextually to support active learning. This study aims to determine the effectiveness of using LKPD in enhancing students’ curiosity in Grade VII Science learning at SMPN 1 Sanrobone. The research employed a Classroom Action Research (CAR) approach carried out in two cycles, each consisting of planning, implementation, observation, and reflection stages. The findings indicate a significant increase in students’ curiosity after the implementation of LKPD, as shown by improvements in questioning behavior, interest in the material, and the ability to observe and explore scientific phenomena. Based on these results, it can be concluded that the use of LKPD is effective in fostering students’ curiosity and contributes to a more interactive and meaningful Science learning experience.

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.

The integration of Artificial Intelligence (AI) in higher education has led to the increasing use of AI-powered adaptive learning models that support personalized and data-driven learning. However, studies examining preservice teachers’ perceptions of these models remain limited, despite their important role in future classroom implementation. This study aims to explore preservice teachers’ perceptions of AI-powered adaptive learning in higher education, focusing on perceived usefulness, learning adaptivity, learning experience, and perceived concerns. A descriptive qualitative research design was employed involving 53 preservice teachers from various universities. Data were collected using a Likert-scale questionnaire and open-ended questions. Quantitative data were analyzed descriptively using percentage distributions, while qualitative data were examined through simple thematic analysis. The findings reveal that preservice teachers generally demonstrate positive perceptions of AIpowered adaptive learning, particularly in terms of learning effectiveness, adaptability, and engagement. Nevertheless, concerns related to over-reliance on AI, ethical issues, and data privacy were also identified. These results indicate that preservice teachers show readiness to engage with AI-supported learning, while highlighting the need for teacher education programs to promote responsible and pedagogically informed AI integration.

This study aims to describe and analyze the implementation of contextual Islamic Religious Education (PAI) based on agro-education integrated with Islamic values at SMP Nurul Huda Merakurak. The background of this research is the need for a more practical and contextually relevant PAI learning model that aligns with students’ real-life environments, particularly in agrarian-based schools. This study employs a qualitative approach using a case study method. Data were collected through observation, in-depth interviews, and documentation. The results show that PAI learning is directly integrated into agro- educational activities such as plant cultivation, environmental management, and character building through values such as trustworthiness (amanah), hard work, responsibility, and gratitude. PAI teachers play an active role in connecting Islamic teachings with agro-educational practices through contextual and reflective approaches. This research contributes to the development of a contextual and transformative PAI learning model that is relevant to local potential and students’ spiritual needs. The findings are expected to inspire other educational institutions in designing innovative PAI learning models based on environmental engagement and character development.

Background: The development of industrial technology in the Industry 4.0 era has encouraged the implementation of intelligent monitoring systems to improve machine reliability and operational efficiency. However, machine fault diagnosis systems based on artificial intelligence often face limitations in terms of interpretability because the models used are complex and difficult to explain. Objective: This study aims to develop a deep learning-based industrial machine fault diagnosis system integrated with an Explainable Artificial Intelligence (XAI) approach to improve diagnostic accuracy while providing interpretable insights for users. Method: The research method involves collecting data from industrial machine sensors consisting of vibration signals, temperature measurements, and acoustic signals, followed by data preprocessing and feature extraction processes. The processed data are then used to train a deep learning-based diagnostic model, after which explainability methods such as SHAP or LIME are applied to analyze the contribution of each feature to the model’s prediction results. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results: The results indicate that the proposed deep learning model achieves better performance compared to conventional machine learning methods such as Support Vector Machine and Random Forest. Furthermore, the explainability analysis reveals that vibration amplitude, increases in machine component temperature, and anomalies in acoustic signals are the main factors influencing machine fault detection. Therefore, the proposed system not only improves the accuracy of machine fault diagnosis but also provides transparency in the decision-making process, thereby supporting the implementation of predictive maintenance in smart manufacturing environments.

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.

This study examines the role of teachers as Islamic counselors in addressing various psychological problems experienced by students, such as learning anxiety, academic stress, low self-confidence, difficulty controlling emotions, and social problems such as bullying. Teachers serve not only as instructors, but also as murabbi, mursyid, and moral role models in guiding students' spiritual and emotional development. The study used a qualitative method with a library study approach, where data were obtained through relevant literature related to Islamic counseling, Islamic education, and student psychology. The results of the study indicate that the implementation of Islamic counseling through strategies such as mau'izhah hasanah, tazkiyah an-nafs, prayer and dhikr, empathy development, and collaboration with guidance and counseling teachers and parents has been proven to reduce students' anxiety and stress levels, increase learning motivation, strengthen morals and character, and provide spiritual peace. Thus, teachers play a strategic role in creating a holistic educational environment and supporting students' psychological well-being. In addition, the implementation of Islamic counseling also plays a role in building students' mental resilience in facing academic and social pressures. In the long term, this will strengthen the Islamic values ​​applied in students, while creating a more resilient and noble generation.

The development of technology in the digital era has brought significant changes to global education systems, including in Indonesia. Digital transformation encourages learning models that are more flexible, interactive, and focused on 21st-century competencies. However, this progress also presents various challenges, particularly related to moral degradation among youth, unequal access to technology, and low digital literacy among teachers and students. This study aims to analyze character education models from a global perspective and evaluate the challenges and strategies for their implementation in Indonesia in the digital era. Using a qualitative research method with a library research approach, data were obtained from credible sources such as scientific journals, books, official reports, and national and international educational documents. The findings indicate that developed countries have successfully integrated technology into their curricula, teacher training, and educational policies, resulting in well- established digital learning ecosystems. In Indonesia, digitalization in education has grown rapidly, especially since the pandemic, but still faces obstacles such as limited infrastructure, varied levels of digital competence among teachers, and a lack of integration of digital pedagogy. In addition, student readiness and access inequality in frontier, outermost, and disadvantaged regions (3T) present further challenges in applying global education models

This article explores the concept of a “House of Faith” as a holistic educational framework designed to build students’ character based on religious values. The fundamental idea of the House of Faith is likened to a school environment that provides a comfortable and safe space for students to develop their faith and noble character through learning activities connected to religious teachings. A religious school environment is created through everyday atmospheres that encourage the practice of worship, the presence of religious symbols, and community activities that strengthen students’ spirituality. Programs to reinforce religious spirit include activities such as communal prayers, religious studies, and social projects designed to gradually enhance students’ spiritual awareness. Teachers and educational staff play a highly effective role, acting as role models and facilitators in the learning process. Their approach to instilling faith and moral values involves interactive methods such as group discussions, inspirational stories, and personal reflection, all adapted to students’ developmental stages. Collaboration between the school and parents becomes a key factor in ensuring consistent support. This is carried out through regular meetings, joint workshops, and open communication that reinforces family values. The impact of religious spirit on students can be seen in increased discipline, social empathy, emotional resilience, and stronger academic motivation. However, implementation faces challenges such as limited curriculum time, diversity of student backgrounds, and cultural resistance. These challenges are addressed through solutions, including regular teacher training, program evaluation, and the integration of technology for distance learning. Overall, the article emphasizes that a school functioning as a House of Faith can shape young generations who are not only intellectually capable but also strong in faith and morals, contributing to a more harmonious and meaningful society.