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In the era of the Industrial Revolution 4.0, Islamic Religious Education (PAI) must emphasize not only memorizing religious content, but also fostering advanced thinking skills such as analysis, evaluation, and creativity through the Higher Order Thinking Skills (HOTS) method. This study aims to describe the implementation of HOTS-oriented Islamic Religious Education (PAI) learning at SMAN 2 Banjit, focusing on implementation methods, supporting and inhibiting factors, and their influence on students. This study uses a qualitative descriptive methodology with data collection methods such as observation, interviews, and documentation. The subjects of the study were Islamic Religious Education (PAI) teachers. Data analysis was carried out by means of data reduction, data presentation, and drawing conclusions. The results of the study indicate that Islamic Religious Education (PAI) teachers at SMAN 2 Banjit have implemented host-based Islamic Religious Education (PAI) teaching methods. HOTS-based learning through discussion methods, advanced question and answer, and problem-based learning, but the implementation has not been evenly distributed across classes. Teachers understand the basic concepts of HOTS, but still face obstacles in preparing HOTS-based learning devices and assessment instruments. Supporting factors for implementation are the support of the principal, technological facilities, and the enthusiasm of some students. Meanwhile, emerging obstacles include a rote-oriented learning culture, unequal distribution of learning facilities, and teacher administrative burdens. The implementation of HOTS has a positive impact on improving students' critical thinking skills and argumentative skills, as well as helping them understand Islamic values ​​more contextually.

Empowering agricultural human resources is a strategic approach to support sustainable agricultural development and the achievement of the Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger), SDG 4 (Quality Education), and SDG 8 (Decent Work and Economic Growth). This community service article aims to describe the implementation of an agricultural instructor empowerment training program conducted through collaboration between Universitas Negeri Surabaya (Unesa) and the Ngudi Luhur Self-Reliant Agricultural and Rural Training Center (P4S) in Blitar Regency. The activity involved approximately 50 participants consisting of agricultural instructors and local agricultural practitioners. The methods included Focus Group Discussions (FGDs) and field visits to superior corn cultivation areas managed by P4S. The results indicate an increase in participants’ understanding of the importance of agricultural innovation and technology utilization to enhance productivity, supported by experiential learning through direct observation of high-yield corn fields compared to conventional practices. This program strengthens the role of agricultural instructors as innovation dissemination agents and contributes to the achievement of sustainable development goals in the agricultural sector.

Innovation in biology learning is increasingly necessary, as conventional instructional practices are often dominated by memorization-based methods that limit students’ active engagement and critical thinking development. Along with rapid advances in science and technology, digital applications offer new opportunities to enhance teaching and learning processes. One such application is Canva, a digital design platform that can be utilized as an effective learning media to support teachers and students in biology education. This study aims to describe the implementation of Canva-based learning media through a training program conducted at SMA Islam Terpadu Daarul Rahman and to examine its perceived usefulness for both teachers and students. The training involved teachers in developing biology learning materials using Canva by integrating visual elements, images, and videos to present complex biological concepts more clearly. The results of the training indicate that Canva is considered practical, user-friendly, and efficient by teachers in designing learning materials. Teachers reported that the application helped them present content in a more attractive and structured manner. Furthermore, students benefited from the use of Canva-based materials, as they demonstrated better understanding of the subject matter and increased interest in learning biology. The integration of visual and multimedia elements also supported the development of students’ critical thinking skills by encouraging analysis and interpretation of biological phenomena. Overall, the use of Canva as a learning medium shows potential to enhance the quality of biology learning and foster more meaningful learning experiences.

This study aims to analyze the effectiveness of the application of direct and indirect methods in teaching English, specifically the topic of "Telling Time," at MTs Al-Amiriyyah through microteaching practice. This research employs a descriptive qualitative approach with data collection techniques including observation, interviews, and documentation. The research subjects consist of an English teacher and the students of class VIII A. The data were thematically analyzed to identify significant patterns in the teaching process. The findings indicate that the direct method is effective in building students' foundational understanding of time concepts, as it emphasizes explicit and concrete use of the target language and allows teachers to easily assess students' comprehension through drilling. On the other hand, the indirect method proved to enhance students’ ability to use English more naturally through contextual activities such as role play and daily schedule games. Moreover, students with kinesthetic learning styles responded more positively to the indirect method, as it enables them to learn through physical activity and direct participation. These findings suggest that a combination of both methods yields optimal results: the direct method is effective for the initial stage of concept acquisition, while the indirect method supports the development of communicative skills in a functional and enjoyable manner, aligning with students' characteristics.

Heritage language loss among immigrant and diaspora communities represents a critical challenge to cultural identity, intergenerational communication, and cognitive diversity. Traditional heritage language maintenance approaches face significant barriers including limited resources, lack of qualified instructors, geographic dispersion, and competing demands of dominant language acquisition. This study investigates the effectiveness of bilingual digital story applications as innovative tools for heritage language maintenance among children aged 4-12 years. Through a 24-month longitudinal mixed-methods study involving 1,843 families across eight language communities (Spanish, Mandarin, Arabic, Korean, Tagalog, Vietnamese, Hindi, and Polish), we examined language proficiency development, cultural identity formation, family engagement patterns, and app usage behaviors. Quantitative analysis of pre- and post-intervention language assessments revealed statistically significant improvements in heritage language vocabulary (effect size d=0.68), listening comprehension (d=0.54), and oral production (d=0.47) among children using bilingual story apps for at least 20 minutes daily. Qualitative findings from parent interviews and child focus groups highlighted the apps' role in making heritage language learning enjoyable, facilitating parent-child interaction, connecting children to cultural narratives, and normalizing bilingualism. However, effectiveness varied substantially based on app design features, with interactive elements, culturally authentic content, parent involvement scaffolds, and adaptive difficulty showing strongest associations with outcomes. This research demonstrates that thoughtfully designed bilingual story apps can serve as accessible, scalable tools for heritage language maintenance, though they function most effectively as complements to rather than substitutes for rich home language environments and community connections. The study contributes empirical evidence to inform app development, family language planning, and policies supporting linguistic diversity in increasingly globalized societies.

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

This study aims to develop an interactive digital learning media based on Wordwall, named TANGKAS (Tantangan Asyik Ngulik Pecahan Kelas Empat Seru), as a practice tool for addition and subtraction of fractions in fourth-grade elementary students. The development process employed the ADDIE model, which includes the Analyze, Design, Develop, Implement, and Evaluate stages. The research subjects consisted of 29 fourth-grade students at SDN Ngemplak I Baureno. The needs analysis revealed that learning activities were still dominated by conventional methods with limited use of digital media, resulting in low student engagement. To address this issue, TANGKAS was developed using a maze chase game design to enhance motivation and support engaging fraction practice. The validation results indicated a material validity score of 94% (highly valid) and a media validity score of 80% (valid). The practicality aspect obtained 81.8% from students, both categorized as highly practical. The effectiveness test showed an improvement in learning outcomes with N-Gain scores of 0.6 for fraction addition and 0.54 for fraction subtraction, both classified as moderate. Therefore, TANGKAS is proven to be feasible, practical, and effective as an interactive game-based learning media to support students’ understanding of mathematics in elementary school.

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

This study aims to enhance elementary school students’ motivation to learn English and to identify the factors contributing to their low motivation. The research is grounded in the need to prepare students for the global era, in which English proficiency is an essential skill from an early age. The study employs a Classroom Action Research (CAR) method using the Kemmis and McTaggart model, consisting of planning, action, observation, and reflection stages. Data were collected through observations, learning outcome evaluations, and interviews with English teachers. The findings reveal that students’ low motivation is influenced by perceptions that English is difficult, the lack of engaging teaching methods, limited learning facilities, and students’ weak willingness to learn. The implemented actions—such as using songs, educational games, teaching aids, role-play activities, and interactive communication—significantly increased students’ activeness and motivation. Moreover, the study emphasizes the importance of introducing English at the elementary level, as ages 6–13 represent a critical period for language development. With appropriate external motivation and strong teacher support, English learning becomes more effective, enjoyable, and meaningful. This study recommends that English instruction continue to be implemented in elementary schools through creative teaching methods and sufficient learning facilities

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 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.

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 aims to analyze the effect of the implementation of the Intelligent Tutoring Sistem (ITS) based on Artificial Intelligence (AI) on improving the understanding of mathematical concepts, especially in fractional and basic geometry materials, in Class V students of SD Negeri 2 Badran, Temanggung Regency. The research method used was a quasiexperimental experiment with a Non-equivalent Control Group Design. The research sample consisted of 48 students who were divided into two groups, namely the experimental group (n=24) who received learning with the help of AI-based ITS, and the control group (n=24) who received conventional learning with lecture methods and practice questions. The research instrument is in the form of a test of understanding of mathematical concepts that has been validated by experts and tested for reliability. Data were analyzed using parametric statistical tests of the Independent Sample t-test and N-Gain Score to measure the improvement. The results showed that there was a significant difference in understanding of mathematical concepts between the experimental group and the control group. The average post-test score of the experimental group (82.45) was significantly higher than that of the control group (70.12) with a p< value of 0.05. N-Gain analysis showed that the improvement in conceptual understanding in the experimental group was in the "moderate" category (g=0.56), while the control group was in the "low" category (g=0.32). These findings indicate that AI-based ITS is effective in improving students' understanding of mathematical concepts. The advantages of the system lie in its ability to provide instant feedback, personalize materials according to learning pace, and present interactive materials, thus helping to better construct students' conceptual understanding. It is recommended that schools consider the integration of ITS technology as a supplementary tool in mathematics learning at the elementary level.

The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netflix Shows dataset, consisting of 8,809 content entries, with the primary features analyzed including genre, rating, and country of production. The research process begins with data exploration and preprocessing stages, including data cleaning, handling missing values, and transforming categorical features to enable effective model construction. Subsequently, the dataset is divided into training and testing sets to objectively and systematically build and evaluate the Naive Bayes classification model. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics to assess the model’s ability to accurately distinguish between Netflix content types. The experimental results demonstrate that the Naive Bayes algorithm is able to classify Netflix content into Movie and TV Show categories with accuracy, precision, recall, and F1-score values of 100%, respectively. The confusion matrix indicates that no misclassification occurred, suggesting that genre, rating, and country of production features provide a very clear separation between content classes. These findings indicate that the Naive Bayes algorithm can achieve exceptionally high classification performance with optimal evaluation results. The results further reveal distinct differences in characteristics between movies and television shows based on genre and production attributes. Therefore, this study is expected to contribute to the development of content recommendation systems and strategic content management within the streaming industry.

AImbalanced data remains a significant issue in heart disease classification using machine learning, as it tends to cause models to overestimate the majority class while ignoring minority classes with high clinical value. This can lead to a decrease in accuracy and the model's ability to accurately detect disease cases. Therefore, this study aims to assess the effectiveness of oversampling techniques, namely Random Oversampling and Synthetic Minority Oversampling Technique (SMOTE), in improving the performance of the K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF) algorithms. The dataset used comes from Kaggle and consists of 918 data sets with 12 attributes representing patient information related to heart disease prediction. The research stages include data preprocessing, baseline model testing, and re-evaluation using the two oversampling methods. Experimental results show that oversampling can improve the performance of all algorithms. KNN achieved the best results with SMOTE, with an accuracy of 72.98% and an F1-score of 75.39%. In the Naive Bayes algorithm, both oversampling techniques produced relatively stable performance, with the highest F1-score of 73.56% using SMOTE. Meanwhile, Random Forest showed the most optimal performance when combined with Random Oversampling, with an accuracy of 79.19% and an F1-score of 81.51%. These findings confirm that the success of data balancing techniques is strongly influenced by the characteristics of the classification algorithm used, and provide a practical contribution in determining strategies for handling imbalanced data in health research.

This study aims to evaluate the impact of role-playing methods on learning interest and number concept mastery in 4-5-year-old children at TK Inomata, Suwawa Selatan District, Bone Bolango Regency. The approach used is a quantitative experimental method with purposive sampling of 8 children, and data collection was carried out through observations of aspects such as enjoyment, focus, activity, and enthusiasm, using a 1-4 scale. The results show that the average learning interest score using the traditional method was only 5.86 (low category), with details: enjoyment 1.71, focus 1.29, activity 1.29, and enthusiasm 1.57. In contrast, the role-playing method of trading/store games showed an average score of 13.86 (very good category), with details: enjoyment 3.57, focus 3.43, activity 3.29, and enthusiasm 3.57. This significant improvement indicates that the role-playing method is more effective in creating interactive, enjoyable, and contextual learning, as well as supporting number comprehension through everyday activity imitation and social skill development. It is recommended to routinely apply this method in early childhood education (PAUD) with adequate teaching aids, as well as involve parents to support the holistic development of children during the golden age.

This study presents a high-accuracy real-time soft failure detection framework for large-scale fiber-to-the-home(FTTH) optical access network using a hybrid ensemble of Isolation Forest and One-Class Support Vector Machine (OCVSM). The proposed model was trainde and validated on a real-word multivariate performance dataset comprising more than 1.8 million samples collected at 5-minute intervals from 50 Optical Line Terminal (OLTs) and over 3,000 Optical Network Terminals (ONTs) across a five-month periode(June-October 2025). Ground-truth validation was performed using 111 confirmed network incidents in October 2025 affecting 12,990 customer. The hybrid ensemble achieved Precision 0.940, Recall 0.982, with an average detection delay of only 7.8 minutes-representing an 87.7% reduction compared to conventional manual response (63.5 minutes). The framework significantly outperforms traditional threesholding and recent ML-based methods while demonstrating practical deployability in live operational enviroments.

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 aims to analyze the effect of the use of kahoot game media on the cognitive learning outcomes of moral beliefs in grade VII C MTS negeri 1 Tuban students. The background of this research is the low enthusiasm and learning outcomes of students in learning moral beliefs which are still dominated by conventional methods while the characteristics of agency students demand a more interactive and adaptive learning approach to technology. This study uses a quantitative approach with a quasi-experimental design of one group pretest design involving 34 students as a sample. This research instrument is in the form of a multiple-choice cognitive learning outcome test of 20 questions covering 4 levels of bloom taxonomy, namely remembering, understanding, applying, and analyzing. The data was analyzed using descriptive statistics and normalistic calculations, the results of the study showed a significant increase in students' cognitive learning outcomes where the average class score increased from 66.03 in the pre-test to 80.29 in the post-test with an engine value of 0.42 which was in the medium category. These findings identify that kahood media has a positive impact on improving students' cognitive learning outcomes.

Digital literacy is important in education in the era of Society 5.0, because teachers are required to be facilitators in supporting students to become digital learners. To support the success of students in becoming digital learners, the role of teachers in the use of technology during learning activities also contributes. The existence of these demands makes the use of virtual reality media in the learning environment an alternative that can be done to create learning activities that meet the demands in the Society 5.0 era. The purpose of this service activity is to improve the digital literacy of IGI Pekanbaru. as well as introduce virtual reality-based learning media as a renewable learning media innovation to support student learning activities in the digital era. In this service, the methods include presentation, demonstration, and practice. The results showed that teacher training in making VR learning media can improve their digital literacy. This training can also help teachers create interactive and interesting technology-based collaborative learning media for modern learning.