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This research aims to improve the understanding of Fiqh subject on mandatory bathing material for fourth-grade students at MI At Thayyibah Banjar Regency through the implementation of the Student Teams Achievement Division (STAD) cooperative learning model with audiovisual media integration. The research subjects were 15 fourth-grade students consisting of 8 male and 7 female students. This study used a classroom action research approach with the Kemmis and McTaggart spiral model conducted in two cycles. Data collection techniques included participatory observation, comprehension tests, semi-structured interviews, and documentation. The results showed a significant improvement in student understanding, marked by an increase in classical mastery percentage from 40% in the pre-cycle to 67% in the first cycle and 87% in the second cycle. The class average score also increased from 68.7 in the pre-cycle to 75.8 in the first cycle and 83.2 in the second cycle. Student learning activities increased from 39.2% in the pre-cycle to 65.4% in the first cycle and 85% in the second cycle. The implementation of the STAD cooperative learning model with audiovisual media proved effective in improving student understanding through creating a collaborative learning environment, concrete material visualization, and active student involvement in knowledge construction. This research provides important implications for developing more innovative and contextual Fiqh learning strategies at the Islamic Elementary School level.

This study aims to develop a hypothetical model of Balai Latihan Kerja (BLK) / Job Training Center through the POAC (Planning, Organizing, Actuating, Controlling) approach as a fundamental framework in reforming the vocational training system. Using qualitative methods with data triangulation from expert interviews, empirical studies, and international reports, the study identified four key themes that determine the effectiveness of the model: digital transformation, strengthening triple helix partnerships, sustainable competency development, and industry-based standardization and certification. Digital transformation through virtual reality-based simulations and digital learning platforms has increased training effectiveness by up to 48%. Triple helix partnerships increase graduate absorption rates by up to 78%. Sustainable competency development is essential, considering that 65% of jobs in 2030 will require skills that do not yet exist today. Industry-based standardization positively correlates with labour productivity, increasing it by 24%. The hypothetical Balai Latihan Kerja (BLK) model that integrates these four themes is expected to be a reference in preparing an adaptive, competitive workforce that is ready to face global challenges in the era of technological disruption.

The aim of this research is to determine the increase in interest in learning for fourth grade students in science subjects with the topic of discussing the characteristics of plants on Ceremai trees through the Quantum Teaching Learning Model at SDI Duarato for the 2024/2025 academic year. This type of research is Classroom Action Research (CAR). The subjects of this research were 15 grade IV students at SD Inpres Duarato, consisting of 8 male students and 7 female students. The object of this research is Natural Sciences (IPA) learning using the Quantum Teaching learning model. Based on research and data analysis, it can be concluded that the Quantum Teaching learning model can increase interest in learning science in class IV students at SD Inpres Duarato for the 2024/2025 academic year. This can be seen before implementing the Quantum Teaching learning model in science learning. Of the 15 students, 6 students (40%) completed it, and 9 students (60%) did not complete it. Furthermore, by applying the Quantum Teaching learning model, it was obtained that 9 students (60%) had completed their learning interest in cycle I, while 6 students (40%) had not completed it. In cycle II, 13 students (86.66%) completed it, and 2 students (13.33%) did not complete it. From the data above, there was an increase from the initial data, cycle I and cycle II.

Learning Islamic Cultural History (SKI) at Madrasah Aliyah presents unique challenges, particularly in increasing students' interest and learning outcomes. Conventional methods such as lectures and memorization often result in low student engagement, leading to suboptimal understanding and poor learning outcomes. To address this issue, this study implements project-based learning (PjBL) as an alternative approach to enhance student learning outcomes. This study examines the effectiveness of project-based learning in improving student achievement in SKI subjects at Madrasah Aliyah 1 Kampar, specifically in class XI Science. Using the Kemmis and McTaggart classroom action research (CAR) model, the research was conducted in two cycles, involving planning, implementation, observation, and reflection stages. Data were collected through learning outcome tests, observation sheets, interviews, and student and teacher questionnaires. Both quantitative and qualitative analyses were performed to comprehensively assess the effectiveness of this method. The findings indicate that implementing project-based learning positively impacts student learning outcomes. The average student score increased significantly from the first to the second cycle. Moreover, student engagement in learning activities improved, as seen in their active participation in discussions, material exploration, and teamwork on assigned projects. Additionally, this method helped students develop critical thinking, problem-solving, and collaboration skills essential in modern education. The study confirms that project-based learning is an effective strategy for enhancing SKI education in Madrasah Aliyah. These findings suggest that educators should adopt more innovative and interactive teaching methods to foster student engagement and deeper understanding in learning.

Study explores the integration of eco theology into Christian higher education curricula, focusing on the role of faith based environmental education in fostering environmental stewardship. Introduction: As the global ecological crisis intensifies, there is a growing need to incorporate ecological ethics into religious education, preparing future leaders to address environmental challenges. By integrating eco theology with sustainability practices, students are encouraged to view environmental stewardship as a spiritual responsibility grounded in biblical teachings. Literature Review: Previous studies emphasize the success of faith based educational approaches in raising ecological awareness and fostering sustainable practices, particularly in Islamic and Christian communities. Eco theology combines theological principles with environmental ethics, offering a holistic perspective on sustainability. Materials and Method: This study employs a mixed methods approach, combining qualitative and quantitative data from interviews, surveys, and focus groups with students and faculty members at Christian institutions that integrate eco theology into their curriculum. The research examines changes in students' attitudes toward sustainability before and after participation in eco theology courses, focusing on practical applications of creation care. Results and Discussion: The findings indicate that the integration of eco theology significantly enhances students' ecological awareness and commitment to sustainability practices. Students report an increased understanding of the ethical and moral responsibility to care for creation, as well as greater engagement in community based conservation efforts. The results highlight the potential of eco theology as a transformative model in Christian higher education, equipping students with both ethical and practical tools to address the global ecological crisis.

This research aims to identify and analyze the essential instructional tools needed in gas turbine learning for cadets of the Naval Academy's engineering corps using a mixed-method approach with an explanatory sequential design involving 160 respondents, consisting of 120 engineering corps cadets, 15 instructors, and 25 field engineering officers. The research results identified 28 types of gas turbine instructional tools categorized into four groups, with simulators and software showing the highest level of importance (4.65/5.0), and there were significant differences in the perception of importance levels among the three groups of respondents (F(2,157) = 12.45, p < 0.001). The AHP analysis produced a priority framework in four levels, with Level 1 encompassing 5 essential instructional tools: gas turbine simulator (0.742), gas turbine cut-section model (0.698), control system trainer kit (0.681), interactive learning video (0.673), and troubleshooting simulator (0.667). Regression analysis showed that instructional tools significantly contribute to learning effectiveness (R² = 0.742), with the gas turbine simulator as the main predictor (β = 0.384), positively impacting the cognitive aspect with a 26.8% increase in concept understanding (effect size 1.24), the affective aspect with an increase in learning motivation and career interest from 67% to 84%, and the psychomotor aspect with a 33.7% increase in hands-on skills and a 28.5% reduction in troubleshooting time. The resulting priority framework provides strategic guidance for optimizing resources and gradually developing gas turbine learning capabilities in military educational institutions, despite facing major obstacles such as budget constraints, technology compatibility, lack of quality human resources, and limited laboratory infrastructure.

The quality of education is one of the important issues that draws attention in various educational discussions in Indonesia. In educational organizations, as in any other organization, achieving good and effective organizational performance becomes the focus of education managers. The impacts of globalization, the development of science and technology, and modern learning models and methods are all contributing factors. This research refers to literature research. To obtain research data, the researcher collects, analyzes, and compiles sources from articles, books, and previous research papers on the application of strategic management in education. The researcher then supplements the strategic management data to improve the quality of education. Teachers and economic policy researchers have started meeting to discuss policy changes in management and how to respond to them. To achieve superior organizational performance, an organization must be able to compete in both human resources and finances. Both are crucial elements for an organization. The role of leadership is a key element in achieving this goal. Improving the quality of education in educational institutions, addressing global challenges, enhancing the quality of educational management, improving the quality of the learning process, improving the quality of human resources in education, as well as strategic management and operational management in building network management.

The problem in this research is the lack of variation in learning carried out by teachers in the classroom, due to the inappropriate selection of learning models, so that learning is less than optimal. The aim is to evaluate how effective the Discovery Learning learning model is in increasing student understanding compared to conventional learning methods. The method used is an experiment with a quasi-experimental design, namely Nonequivalent Control Group Design. In this study, there were two groups: an experimental group that was taught using Discovery Learning and a control group that was not given this treatment. The population of this study were all 5th grade students at MIN 1 Soppeng. The research hypothesis analyzed using the T test is the statement that the Discovery Learning learning model influences student learning outcomes. The sample in this study was determined by a saturated population, namely 5th grade students consisting of 45 people. The data collection techniques used in this research were multiple choice tests and observation sheets, with pre-tests and post-tests to measure students' cognitive learning outcomes. The instruments used in this research were tests and non-tests. The average pretest score in the experimental class and control class was almost the same, 71.78 and 71 respectively, but in the posttest, the experimental class increased to 88.65, while the control class only reached 77.55. Thus, the experimental class experienced a more significant increase in the average posttest score compared to the control class, indicating that the intervention or treatment applied in the experimental class was more effective in improving student learning outcomes. Hypothesis testing based on t-test analysis shows significant differences between the two groups, where the calculated t value (11.22771) is greater than the t table (2.016692), so the null hypothesis (H_0) is rejected and the alternative hypothesis (H_1) is accepted. These findings show that the Discovery Learning learning model has a greater positive impact on improving student learning outcomes compared to conventional methods, so it can be concluded that this method is effectively used in science learning at MIN 1 Soppeng.

This research aims to develop and test the feasibility of products in the form of heyzine flipbook-based learning media in the subject of Lathe Machining Engineering class XI at SMK Kemala Bhayangkari 1 Jakarta. This learning media was developed using the R&D (Research and Development) method using a 4D model consisting of define, design, develop, and disseminate. In the process of assessing the feasibility of this learning media, it provides a validation assessment questionnaire instrument to material experts, media experts, and media feasibility tests to students in grade XI of Machining Engineering as respondents. Learning media is validated by experts with a score of 100% for the material aspect, 94% for the media aspect. And for the results of the feasibility trial, the learning media got a score of 91% of the results of the trial of 53 students. From the results of the test, it can be concluded that the heyzine flipbook-based learning media in the Lathe Machining Engineering class XI subject at SMK Kemala Bhayangkari 1 Jakarta is "Very Feasible" to be used for Lathe Machining Engineering learning activities. The focus of this study is at the stage of development and feasibility testing of the developed media only, as for the results of this study, there are several recommendations that can be given, including the following, heyzine flipbook-based learning media can be implemented and utilized optimally in the learning process of Lathe Machining Engineering at SMK Kemala Bhayangkari 1 Jakarta and other schools where there are Lathe Machining Engineering subjects. And heyzine flipbook-based learning media in the subject of Lathe Machining Engineering needs to be further researched such as the effectiveness of heyzine flipbook-based learning media in the subject of Lathe Machining Engineering.

This study aims to analyze the models and strategies of prose teaching, specifically Hikayat, at SMK Negeri 4 Medan. The teaching of prose plays a significant role in enhancing students' literacy, deepening appreciation for literary works, and instilling moral and local cultural values. The method used in this study is descriptive qualitative, which includes observation, interviews, and documentation, with an emphasis on the implementation of teaching strategies by Indonesian language teachers. The results of the study show that the learning process at this vocational school faces various challenges, such as low student interest and limitations in literacy. To address these issues, teachers integrate theory with practice, utilize multimedia-based technology, and implement group discussions to encourage active student participation. Evaluation is conducted through student work presentations, combining literacy assessment and speaking skills. Recommendations from this study include the development of innovative, technology-based approaches and increased student engagement in the learning process to create more effective and meaningful learning experiences.

This research is motivated by the challenges in facial identification for forensic investigations due to poor image quality, especially from low-resolution CCTV recordings. Images with noise, low lighting, and suboptimal angles often hinder accurate facial recognition. This study aims to examine the effectiveness of the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) method in enhancing the quality of forensic facial images. The methodology consists of three main stages: data preparation of low-resolution facial images, applying the ESRGAN model to enhance image resolution, and evaluating the results using metrics such as PSNR and SSIM. The findings reveal that ESRGAN significantly improves the visual details of facial images, thereby supporting better facial identification processes. These results have important implications for leveraging deep learning technology to facilitate image analysis in forensic contexts. However, challenges such as extreme noise presence require further development of methods to achieve more optimal outcomes.

This research aims to design syntax in literature learning using the Project Based Learning (PjBL) model at UPT SMP Negeri 17 Medan. This research focuses on the effectiveness of applying PjBL syntax in improving students' literary understanding, critical thinking skills and creativity. This research uses a qualitative descriptive method with data collection techniques through observation, interviews and documentation. Research findings reveal that the application of the PjBL model in literature learning has a positive impact on student engagement and in-depth understanding of literary material. Project-based evaluations also help students develop collaboration and communication skills. Systematic implementation of PjBL syntax provides a clear and effective learning structure, thereby improving the overall quality of learning.

This study discusses the application of the cooperative learning model in improving students' ability to learn drama at Istiqlal Delitua Private High School. In this case, the cooperative learning model is one of the learning models used in drama learning because this model can encourage collaboration, improve social skills, and develop student creativity. This study also uses a qualitative descriptive method with data collection techniques in the form of observation, interviews, and documentation. The results of the study show that the application of the cooperative learning model significantly improves student engagement, drama script writing skills, and character acting skills. This model is also effective in creating an interactive and fun learning atmosphere, increasing student motivation, and building confidence in drama performances. This study also emphasizes the importance of teacher support and a conducive environment in implementing a cooperative learning model for drama learning.

This research develops a fruit classification system using Convolutional Neural Network (CNN) in the educational application FruityLens, which helps children recognize different types of fruits through image recognition. The application can identify four types of fruits: apple, banana, orange, and watermelon, utilizing an image dataset from open sources. The research methods include dataset collection, image pre-processing, CNN model training, and classification accuracy evaluation. The results indicate that the developed CNN model achieves high accuracy, supporting children's learning about fruits. This implementation is expected to contribute to the advancement of artificial intelligence technology, specifically in the field of fruit object recognition.

This research investigates school scope classification using Deep Neural Networks (DNN), focusing on students living environments and educational opportunities. By addressing the interplay of socioeconomic and educational factors, the study aims to develop an analytical framework for understanding how environmental contexts shape academic trajectories. The research provides a nuanced understanding of the importance of features in educational classification by developing DNN models based on Spearman's Rank Correlation Coefficient (SRCC). The methodology employs machine learning techniques, integrating data wrangling, exploratory analysis, and multiple DNN models with K-fold cross-validation. The study analyzes 677 student records from two schools. The research examined multiple model configurations. Results show that the 'All Data' model achieved 83.08% accuracy, the 'Top 5' model 81.54%, and the 'Non-Top 5' model 79.23%. The SRCC-based approach revealed that while top correlated features are important, additional variables significantly contribute to model performance. The study highlights the profound impact of family background, social environment, and educational contexts on school selection. Furthermore, it demonstrates DNN's capability to uncover intricate, non-linear relationships, offering actionable insights for policymakers to leverage machine learning's potential in developing targeted educational strategies.

Dengue fever (DHF) is an infectious disease caused by the dengue virus and transmitted through the bite of the Aedes aegypti mosquito. This disease is a major health problem in many tropical countries, including Indonesia. Identification and classification of DHF patients is very important to prevent further spread and to provide appropriate medical treatment. In this study, the classification of DHF disease is carried out using the K-Means algorithm, which is one of the methods in machine learning used to classify data based on similarity of features. This study aims to apply the K-Means algorithm in classifying DHF cases based on data on symptoms that appear in patients, such as high fever, joint pain, skin rashes, and others. The data used includes patient medical records that record various clinical and demographic parameters. The K-Means algorithm is used to group the data into clusters that describe the severity category or potential risk of dengue disease. The results showed that the K-Means algorithm can be used to cluster DHF patients well, with the division of groups that can describe the severity of the disease. Evaluation was conducted using metrics such as silhouette and cluster validity to assess the effectiveness of the algorithm in performing classification. This model is expected to help medical personnel in decision-making, provide early warning, and improve rapid response to dengue cases.

Computer vision technology has advanced rapidly and made significant contributions across various fields, including object identification in images. This study aims to develop a computer vision-based system to identify fruit types from images. A machine learning model is applied using a dataset of fruit images to train the system for accurate fruit recognition. The primary processes include data acquisition, image preprocessing, feature extraction, model training, and performance evaluation. The results demonstrate a high level of accuracy in identifying specific fruit types, showcasing the potential of this technology in agricultural and commercial applications.

This quantitative study aims to discover the effect of the Process Oriented Guided Inquiry Learning (POGIL) learning strategy on students' science process skills concerning reaction rate material. The study employs a quasi-experimental design with a pre-posttest control group. The instrument used is a multiple-choice test to measure students' science process skills. The sample consists of all students in the XI IPA class at SMA Negeri 5 Gorontalo, totaling 45 students: 22 in the experimental group and 23 in the control group. Data analysis utilizes the Rasch Model and SPSS 16.0 for hypothesis testing using the Wilcoxon test. The analysis results show that the person reliability value is 0.00, indicating weak consistency in answering the questions, while the item reliability value is 0.71, suggesting that the quality of the test items is quite good. The mean difference in item scores from pre-test to post-test is greater in the experimental group (3.83 logit) compared to the control group (1.59 logit). Wilcoxon test results show significant values < 0.05, with the experimental group having a significant value of 0.00 and the control group at 0.00.

The objectives of this research are: (1) Producing interactive learning media based on articulate storyline 3 in high school accounting learning subjects. (2) Producinh interactive learning media based on articulate storyline 3 which is feasible in learning high school accounting. (3) Knowing the effectiveness of interactive media development based on articulate storyline 3 in high school accounting subjects in increasing students' learning motivation.The type of the research used is research and development with the ADDIE model. The media trial design used a nonequivalent control group experimental design. The feasibility of the product was tested by media experts, material experts, learning practitioners namely teachers, and media users namely students. The media was tested on the research subjects, namely students of class XII IPS 3 SMA N 1 Seyegan. Data collection was carried out by using observation, interviews, and questionnaires. The data collection instruments used interview guidelines, expert validation questionnaire, material validation questionnaire, teacher response questionnaire, student response questionnaire, and student motivation questionnaire. The feasibility of the learning media produced was analysed by using 4 scales, namely very feasible, feasible, inappropriate, and very inappropriate. The results of the study show: (1) Interactive learning learning media based on Articulate Storyline 3 has been successfully developed to increase students‘ learning motivation in high school; (2) Interactive learning learning media based on Articulate Storyline 3 is considered feasible by media experts with a score of 3.66; material experts with a score of 3.47; teacher practitioners 3.65; and students 3.38; (3) Based on the difference in gain score of the experimental group (0.61) from the control which is (0.45), learning media can increase students’ learning motivation.

This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, particularly in high-density urban transportation environments. Therefore, an automated and intelligent solution is required to support real-time monitoring and operational decision-making. The proposed system employs deep learning-based object detection to identify and count passengers from video streams captured by cameras installed inside buses. Two camera positions, namely front and rear views, were evaluated to assess system performance under different visual conditions. The experimental results show that the system achieves high detection accuracy in the front camera view, with a confidence score of 0.82, indicating reliable performance in scenarios with minimal object occlusion. In contrast, the rear camera view demonstrates slightly lower accuracy, with a confidence score of 0.76, mainly due to increased object overlap and variations in lighting conditions. These findings emphasize the importance of appropriate camera placement and environmental consideration in improving detection reliability. In addition, the implementation of the proposed system enables real-time monitoring of passenger flow, which supports dynamic scheduling, demand-based route planning, and efficient fleet management. Accurate passenger data allows transportation operators to optimize service allocation, reduce congestion, and enhance overall service quality. Overall, this study contributes to the development of intelligent transportation systems by demonstrating the practical applicability of deep learning-based passenger counting solutions. The proposed approach offers strong potential for real-world deployment in smart city environments, supporting the creation of more sustainable, efficient, and passenger-oriented public transportation services.