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The expository learning strategy in Islamic Religious Education (PAI) remains relevant as a classical Islamic scholarly heritage but requires creative transformation to address digital-age challenges. This article examines the implementation of expository strategies through literature study, analyzing philosophical foundations, effectiveness, contemporary challenges, and innovation models. The research reveals that expository strategies are effective for normative PAI materials but face complex challenges including shifting cognitive patterns of digital natives, decentralization of knowledge authority, and technological disparities. Various innovative models (interactive, contextual, multimedia, reflective) offer solutions by integrating traditional expository strengths with modern approaches. The study concludes that successful implementation requires paradigmatic reconstruction through "pedagogical ijtihad" balancing Islamic scholarly authenticity with 21st-century learning needs. PAI teachers must master three core competencies: depth of religious knowledge, pedagogical sophistication, and technological literacy. 

This research presents a personalized, context-aware recommender system to suggest Places of Interest (POIs) using a hybrid approach combining Bayesian inference and collaborative filtering. The system explicitly addresses the cold-start problem that new users face and improves recommendation accuracy by considering contextual variables such as user mood, budget, companion, and location. The system collects real-time contextual inputs for new users with no historical data and applies Bayesian inference to generate relevant POI suggestions. As users begin to interact and provide ratings, the system progressively shifts to a collaborative filtering mechanism, leveraging cosine similarity to identify similar users within comparable contexts. The recommender system focuses on three categories of POIs: restaurants, hotels, and landmarks. These locations are retrieved through the Google Maps API, and only mapped locations are considered. The system was implemented on Android devices and evaluated through a user study involving 25 participants from diverse backgrounds, including software developers, IT students, and general users. Evaluation metrics such as normalized Discounted Cumulative Gain (nDCG) and classification accuracy were used to assess recommendation quality. Results demonstrate that the system performs better than traditional methods, with nDCG improvements reaching up to 83 percent. Users reported high satisfaction regarding the recommendations' accuracy, ease of use, and contextual relevance. While the system offers significant improvements, it also has certain limitations. Its dependency on Google Maps data may restrict its scope, and using only four contextual factors limits the system’s adaptability to more complex user preferences. Future enhancements could include additional dynamic contexts such as weather, POI popularity, and time-related trends, as well as integrating more advanced models to increase personalization and flexibility in real-world applications.

This study aims to analyze the role of environmental education in raising ecological awareness and to identify the supporting and hindering factors in its implementation. Using a qualitative approach, data were collected through literature reviews, interviews, and observations at both formal and non-formal educational institutions. The findings indicate that environmental education plays a significant role in shaping environmentally friendly awareness and behavior among learners. It encourages a deeper understanding of ecological issues and fosters a sense of responsibility toward the environment. However, in practice, the implementation of environmental education still faces various challenges. The main obstacles identified include limited resources, a shortage of educators with specific competencies in environmental topics, and a lack of policy support from both government and educational institutions. On the other hand, practice-based learning methods—such as field activities, environmental projects, and collaborations with local communities—have proven more effective in enhancing active participation and engagement among students. The main contribution of this study is to provide insights into optimal strategies for the implementation of environmental education, along with recommendations for policymakers to improve its effectiveness through curriculum strengthening and innovative teaching methods. These findings also serve as a foundation for developing more contextual and applicable learning models. For future research, it is recommended to broaden the scope of the study by examining the effectiveness of environmental education in various socio-economic contexts and exploring the use of digital technologies in environmental learning.

This study uses a qualitative methodology and secondary source data to investigate election cheating and its impact on Nigeria's democratic consolidation. It will be examined using historical and content analysis. examination. Nigerian democracy's progress has been severely hampered by election tampering. According to the report, e-election holds enormous promise and might be the solution to voter fraud in Nigeria's electoral system provided it is properly deployed and funded. It starts by looking at the constitutional, legal, and theoretical underpinnings of electronic voting. Second, it examines the real-world obstacles to the adoption and deployment of an electronic voting system in Nigeria by learning from other countries. Nigeria's elections have fallen short of expectations thus far because of a variety of electoral manipulations that have prevented the nation from holding legitimate, free, and fair elections within her political system. In addition to undermining Nigeria's democratic consolidation, election cheating has breached the fundamental human right (right to lives) of a large number of Nigerians. This essay offers some crucial suggestions that could solve the issues of election tampering and explain how those actions can support the need for a democratic atmosphere,

Understanding of Mathematics concepts is an important factor in determining students' learning success. However, the results of observations at SDN 33 Kalumbuk showed that fifth grade students still had difficulty in understanding Mathematics concepts. This can be seen from the low level of learning completion, which was only 36.84% in class VA and 33% in class VB. The low understanding of concepts is caused by the lack of interactive learning methods, so that students get bored easily and are less involved in the learning process. This article discusses the importance of understanding concepts in Mathematics learning and solutions that can be applied to improve student understanding. One of the proposed strategies is the use of the Make a Match learning model, which can increase student engagement and help them understand concepts more concretely and interestingly. In addition, problem-solving approaches, the use of visual media, group discussions, and continuous evaluation can also be applied to improve learning effectiveness. By implementing innovative and interactive learning methods, it is hoped that students' understanding of Mathematics concepts can improve, so that they are better prepared to face academic challenges and are able to apply Mathematics concepts in everyday life.    

The principal is the highest leader in an educational unit who has the task and responsibility to manage the educational unit, therefore this study aims to describe and analyze the Principal's strategy in implementing educational management and the factors that hinder and support the implementation of the Principal's strategy in implementing educational management and the efforts made by the Principal in overcoming obstacles in the implementation of Educational Management at SMA Bina Warga 1 Palembang. The research data were obtained by interviews, observation and document methods which were analyzed using interactive model analysis. Based on the results of the study, it was concluded that 1) the Principal's strategy in implementing educational management at SMA Bina Warga 1 Palembang implemented the principles and functions of educational management such as planning, organizing, implementing/driving, and supervising, especially in the governance of students, educators and education personnel, and facilities and infrastructure so that the implementation of education runs in accordance with applicable regulations. 2) inhibiting and supporting factors for the implementation of the principal's strategy in implementing educational management at SMA Bina Warga 1 Palembang including the principal's ability in educational management and leadership, support and active participation of educators and educational personnel, availability of adequate facilities and sufficient resources to support the learning process, a positive culture that has grown and developed in the school. While inhibiting factors include budget limitations, less than optimal communication and coordination, educators' understanding of new approaches to changing school conditions, and parental support that is not yet complete. 3) efforts made to overcome obstacles to the principal's strategy in implementing educational management at SMA Bina Warga 1 Palembang include optimizing the use of human resources, a persuasive approach to teachers and stakeholders, implementing time management, strengthening collaboration with parents and other stakeholders

This study aims to comprehensively examine the influence of the Problem-Based Learning (PBL) model integrated with the Internet of Things (IoT) on enhancing students’ problem-solving abilities in physics education. The integration of IoT into PBL is seen as a progressive approach to address the growing demand for innovative instructional strategies that promote higher-order thinking skills. A quantitative approach was adopted, utilizing a quasi-experimental design with a pretest-posttest nonequivalent control group format to assess the effectiveness of the intervention. The participants were 25 undergraduate physics students from the University of West Sulawesi, selected through saturated sampling due to the limited population size. To evaluate students’ problem-solving skills, data were collected using structured written tests designed around five key indicators: understanding the problem, describing the problem, planning the solution, executing the solution, and evaluating the results. Prior to hypothesis testing, normality of the data was assessed using the Kolmogorov-Smirnov test, followed by paired sample t-tests with IBM SPSS Statistics 23 to determine the significance of differences in pretest and posttest scores. The findings revealed a statistically significant improvement in students’ problem-solving skills following the implementation of the IoT-based PBL model, with results showing significance at the 5% level and gain scores classified as effective. These outcomes demonstrate the potential of the PBL-IoT integration to foster critical thinking and improve educational quality. Therefore, the implementation of this instructional model is recommended for physics educators seeking to enhance student engagement, problem-solving proficiency, and learning outcomes through the integration of emerging technologies.

This study aims to examine the role of Christian religious education teachers as role models in preventing bullying in the environment of SMA Negeri 2 Siborong-Borong. Bullying in schools is a serious problem that can hurt student's mental and emotional development. As respected figures and role models, teachers have a key role in creating a safe and respectful environment. In this study, the author highlights various ways in which teachers can play an active role, such as being an example of positive behaviour, building good relationships with students, teaching the values ​​of empathy and tolerance, and enforcing anti-bullying rules firmly. The method used in this study is a qualitative approach by presenting descriptions of literature, books and journals that are linked to the context of teachers and students at SMA Negeri 2 Siborong-Borong. The results of the study indicate that the role of teachers as role models is very important in creating a school culture that is free from bullying and increasing students' awareness of the dangers of bullying and the importance of mutual respect. Thus, the role of teachers as role models in preventing bullying can significantly impact creating a safe and comfortable learning atmosphere for all students.

This study aims to describe the improvement of student learning outcomes in science learning using the Problem Based Learning (PBL) Model in Class V of SDN 16 Pulau Karam, Pesisir Selatan Regency. This study is a classroom action research (PTK) with a qualitative and quantitative approach. Implemented in 2 cycles, cycle I consists of 2 meetings and cycle II consists of 1 meeting. The results of the study showed an increase in teaching modules in science learning using the Problem Based Learning (PBL) model, the implementation of science learning using the Problem Based Learning (PBL) model and student learning outcomes in science learning using the Problem Based Learning (PBL) model. This can be seen from the average observation results of the Teaching Module cycle I which was 87.4% (B) increasing in cycle II to 92.8% (SB). This is also seen in the average results of teacher activities in cycle I which were 85.9% (B) increasing in cycle II to 93.8% (SB). In student activities, the average cycle I was 84.3% (B) increasing in cycle II to 93.8%. In student learning outcomes, the average cycle 1 was 81% (B) and increased in cycle 2 to 91%. Based on these results, it can be concluded that using the Problem Based Learning (PBL) model can improve the results of learning science in class V SDN 16 Pulau Karam, Pesisir Selatan Regency.

Artificial Intelligence (AI) in learning can serve as a tool for students to acquire knowledge. However, the understanding and use of AI in education still face various challenges. Some universities have started integrating AI learning into their curricula, but its implementation remains limited and uneven across different institutions. Additionally, the level of AI literacy among students in Indonesia is still relatively low. Adequate AI literacy is crucial for students to optimize the use of this technology without excessive dependence and to understand its ethical implications.This research aims to assess students' understanding of AI literacy and explore how AI literacy education can be integrated with the European model. A mixed-method approach is used in this study, combining quantitative research through questionnaires and qualitative research through interviews. The results indicate that students in Indonesia have a fairly good understanding of AI literacy. However, several challenges remain, including students' dependence on AI and ethical issues related to its use.Therefore, collaboration among various stakeholders, including universities, the government, and industry, is essential to enhance students' AI literacy skills. Efforts can include training programs, providing access to AI resources, and adopting AI-based learning models that have been implemented in Europe. Through these measures, it is expected that students' AI literacy will improve, supporting the advancement of technology-based education in Indonesia.

Aspect-based sentiment Analysis (ABSA) is vital in capturing customer opinions on specific e-commerce products and service attributes. This study proposes a hybrid deep learning model integrating Bi-Directional Gated Recurrent Units (BiGRU) and Bi-Directional Attention Flow (BiDAF) to perform aspect-level sentiment classification. BiGRU captures sequential dependencies, while BiDAF enhances attention by focusing on sentiment-relevant segments. The model is trained on an Amazon review dataset with preprocessing steps, including emoji handling, slang normalization, and lemmatization. It achieves a peak training accuracy of 99.78% at epoch 138 with early stopping. The model delivers a strong performance on the Amazon test set across four key aspects: price, quality, service, and delivery, with F1 scores ranging from 0.90 to 0.92. The model was also evaluated on the SemEval 2014 ABSA dataset to assess generalizability. Results on the restaurant domain achieved an F1-score of 88.78% and 83.66% on the laptop domain, outperforming several state-of-the-art baselines. These findings confirm the effectiveness of the BiGRU-BiDAF architecture in modeling aspect-specific sentiment across diverse domains.

This study aims to examine the implementation of a differentiated learning model in improving maritime English language competency among maritime college students in Indonesia. The background of this study is based on the maritime world's need for graduates with good English language competency, especially in professional and technical contexts. The approach used was a mixed method, namely a combination of quantitative and qualitative methods within a classroom action research framework implemented over two learning cycles. Data were collected through English language competency tests, observations, and in-depth interviews. The results showed a significant increase in all aspects of maritime English competency. The highest increase occurred in speaking skills at 44.38%, while the lowest increase was in maritime vocabulary comprehension at 30.25%. After the implementation of the differentiated learning model, 78.33% of students were in the "Good" and "Very Good" competency categories. Although in the initial stages of implementation there were challenges in students' adaptation to learning methods that differ from conventional learning, these obstacles were successfully overcome through a project-based learning strategy. This strategy is considered the most effective because it is able to provide an authentic context and approximate the real conditions in the maritime workplace. Thus, it can be concluded that the differentiated learning model has proven effective in improving students' maritime English language competency. This study recommends the broader implementation of similar models in English language learning programs at maritime institutions.

Many students find it difficult to connect abstract mathematical concepts with real-world applications, leading to limited problem-solving and modeling skills. This study aimed to develop a real-world problem-based mathematics module designed to enhance students’ mathematical modeling abilities. Using a Research and Development (R&D) approach with the 4D model Define, Design, Develop, and Disseminate the research involved secondary school students enrolled in mathematics classes. The Define stage identified learning difficulties and needs, while the Design and Develop stages focused on creating, validating, and refining a contextual mathematics module based on expert feedback. Quantitative data were collected through expert validation sheets, mathematical modeling tests, and student response questionnaires. The results demonstrated that the developed module achieved a high level of content and design validity, confirming its appropriateness for classroom use. Student responses indicated strong practicality and engagement during implementation. The effectiveness analysis showed a 28% improvement in mathematical modeling skills after the intervention, as evidenced by increased post-test scores and positive student feedback. Compared to traditional textbook-based instruction, the module proved more effective in fostering conceptual understanding, analytical reasoning, and real-world application of mathematics. In conclusion, the developed real-world problem-based module successfully bridges the gap between theoretical mathematics and authentic contexts, providing an innovative framework to cultivate modeling competence and critical thinking among students.

In the current digital era, SMEs in the culinary sector face challenges in adopting technology to improve operational efficiency. One solution to address this issue is the use of a simple and cost-effective QR Code-based application. This study aims to develop and implement siMenu, an application that provides table, order, and product management solutions without integrating complex digital payment systems. The method used is Project-Based Learning (PBL), which allows the development of technical skills while designing a sustainable business model through Business Model Canvas (BMC). The results show that siMenu successfully improved operational efficiency for SMEs, reduced ordering errors, and provided an easy-to-adopt solution with low implementation costs. However, challenges in application development and building user trust remain obstacles. The conclusion of this study is that simple digital solutions like siMenu can help SMEs in the culinary sector digitally transform and stay competitive in an increasingly evolving market.  

This study explores the implementation of Computational Thinking (CT) in physics learning to enhance students' analytical and logical reasoning. Using an experimental approach with a problem-solving model, the research involved students enrolled in physics courses, divided into experimental and control groups. The experimental group engaged in simulation-based and algorithmic problem-solving tasks, while the control group received conventional instruction. The research focused on assessing improvements in logical reasoning through pre- and post-tests. Data analysis was conducted quantitatively, comparing the pre-test and post-test results of both groups. Findings revealed that the experimental group showed a significant 31% improvement in logical reasoning skills, while the control group demonstrated a modest 5.8% improvement. This indicates that CT-based activities, such as simulations and algorithmic tasks, are more effective in enhancing students' analytical and problem-solving abilities compared to traditional methods. The study highlights the importance of integrating CT into physics education, as it promotes deeper cognitive engagement, critical thinking, and practical problem-solving skills. These findings suggest that CT strategies can be a powerful tool in improving students' reasoning abilities and better preparing them for complex scientific and real-world challenges.

This study aims to analyze the implementation of the SPIRIT model of problem-based biology learning (SSIPBL) on the respiratory system material at Muhammadiyah 1 Sragen High School in the 2024/2025 academic year and to determine whether this model can improve students' learning outcomes. The research type used is quantitative with an experimental design. Data collection was carried out through learning outcome tests, observations, and interviews. Based on the t-test results, a significance value (sig.) of 0.198 was obtained, which is greater than the 0.05 value, indicating that there is no significant difference between the experimental group using the SSIPBL model and the control group using conventional learning methods. Factors affecting the ineffectiveness of this model's implementation include teacher readiness, limited time, lack of student involvement, and inadequate infrastructure. The results of this study show that the implementation of the SPIRIT SSIPBL model on the respiratory system material does not significantly improve students' learning outcomes. Therefore, it is recommended to improve supporting aspects, such as teacher training, better time management, and increasing student motivation and involvement in problem-based learning. Indicates that the implementation of the SPIRIT model of Socio-Scientific Problem-Based Learning (SSIPBL) can significantly improve students' learning outcomes on the respiratory system material senior High School for the. These results suggest that SSIPBL has the potential to enhance students' understanding through a problem-based approach that connects scientific phenomena with social issues, and its implementation in the field met expectations.

Learning that is still dominated by teacher-centered approaches tends to result in passive student participation and low learning outcomes. This study aims to compare the effectiveness of the Socio-Scientific Problem-Based Learning (SSPBL) model and the Stimulus Environment Problem Solving (SEPS) model in improving student learning outcomes in the Ecology course. The research employed a quasi-experimental design involving two groups of fourth-semester Biology Education students at Universitas Muhammadiyah Surakarta in the even semester of the 2023/2024 academic year. Each group consisted of 20 students; one was taught using the SSPBL model, and the other using the SEPS model. Data were analyzed using the independent sample t-test and effect size analysis.The results showed that the SSPBL group achieved significantly higher cognitive learning outcomes than the SEPS group in both Cycle I (sig. = 0.041) and Cycle II (sig. = 0.049). The effect size results further confirmed the high effectiveness of the SSPBL model, with values of 2.846 (Cycle I) and 3.413 (Cycle II), categorized as "high." These findings indicate that the SSPBL model is more effective in improving learning outcomes, particularly in developing higher-order thinking skills through the integration of scientific concepts and socio-scientific issues. This study recommends the implementation of the SSPBL model in science education to foster deeper conceptual understanding and critical thinking among students.

The orientation of educational institutions is busy with exam scores, and academic grades are the main prerequisites for graduation. As a result, the product produced by students is how high the report card score is and discredits the values of character, life and morality. This causes students to lose focus on character education. For this reason, teachers as the main milestone in learning in the classroom are required to create a learning atmosphere with character based on DOOR (Diversity, Optimism, Option for The Poor, Respect). This is because the character based on DOOR is a guideline in the ministry at the Bethlehem Bandar Baru Foundation. The objectives of the study are: (1) To describe the management model of character education training based on DOOR; (2) Determine the feasibility of the character education training management model based on DOOR; and (3) Determine the effectiveness of the implementation of character education training management based on DOOR at the Bethlehem Bandar Baru Foundation. The research uses a research and development approach to develop a model to improve teacher performance at the Betlehem Bandar Baru Foundation. The research sample is 59 teachers at the Bethlehem Bandar Baru Foundation. The results of the study show: (1) The training model developed is feasible to be used in an effort to improve the performance of teachers of the Bethlehem Bandar Baru Foundation, through the following stages: planning, organizing, moving, and supervising; (2) The training model is effectively used to improve the performance of teachers of the Betlehem Bandar Baru Foundation. There was an increase in teacher performance in the following aspects: learning planning by 42.05%; the implementation of learning is 29.74%; and assessed learning outcomes by 59.49%; and (3) a character training model developed practically for improving teacher performance at the Bethlehem Bandar Baru Foundation, obtained N-Gain Score g = 0.76 > 0.7 (small group trial) and g = 0.79 > 0.7 (limited wide trial); The resulting products were 76.40% (small group trials) and 79.08% (limited wide trials) with the effective category. Based on the results of the study, it is suggested that the improvement of teacher performance at the Bethlehem Bandar Baru Foundation must be carried out with integrated planning, organization, implementation and supervision between the Archdiocesan Foundation, the Foundation's internal supervisors, principals, and teachers.  

Accurate sales forecasting is essential for stakeholders to make strategic decisions. This study aims to compare the performance of two deep learning models, namely Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), in forecasting domestic motorcycle sales produced by AISI member manufacturers. The forecast is based on historical data from January 2021 to December 2024. The model was trained using time series data and the forecasting results for the period January to March 2025 were evaluated using the metrics Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results show that the LSTM model produces lower MAE and MAPE values than CNN, which shows its superiority in providing more accurate and consistent predictions. On the other hand, the CNN model has lower RMSE and MSE values, thus being able to reduce large prediction errors. By comparing the results of LSTM, CNN, and actual data forecasting, the LSTM model is more suitable for forecasting motorcycle sales in Indonesia

This study aims to measure and analyse the relationship between variables and obtain an accurate picture of the most significant factors in predicting student achievement motivation in online learning including internal, external, type of learning, psychological variables, fatigue variables, and achievement motivation of non Pendas Open University students in online learning. The research approach is ex-post facto quantitative method. With a sample size of 200 people, with research variables internal variables (X1), psychological variables (X2), fatigue variables (X3), external variables (X4), learning type variables (X5) and achievement motivation (Y). Data was collected using a questionnaire with a Likert scale of 1-4. Then the data was analysed using the Partial Least Square (PLS) method by looking at the p-value, by measuring the outer model and inner model. The results showed that external variables have a significant and high influence on achievement motivation with a statistical T value of 3.196, p-value 0.001, and F square 0.104. This indicates that external factors, such as environmental support and facilities, play an important role in motivating students. Internal variables and learning types also have a significant influence with a medium effect strength, indicated by an F square value of 0.061. Internal factors, including self-management and intrinsic motivation, as well as the type of learning methods used, play a moderate role in influencing students' motivation. Psychology also had a significant effect with moderate strength (F square 0.037), signalling the importance of students' mental and emotional state. Meanwhile, fatigue showed no significant effect on achievement motivation (T statistic 0.684, p-value 0.494).