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This research aims to analyze and compare traditional Islamic education systems in Indonesia, Malaysia, and Thailand, focusing on institutional aspects, education systems, learning methods, and curricula. Using a literature study method with a descriptive qualitative approach, this research examines various relevant literature regarding the dynamics of Islamic education in Southeast Asia. The results show that the three countries share fundamental similarities in educational forms, such as pesantren or pondok, which focus on Islamic sciences and moral cultivation. However, significant differences exist in management patterns and the level of integration with government policies. Indonesia maintains a variety of salaf and modern pesantren, Malaysia exhibits a more structured system integrated with the state, while Thailand specifically in the Patani region tends to be adaptive in response to its Muslim minority status. This comparison concludes that the development of traditional Islamic education systems in each country is heavily influenced by the respective social and political contexts.

The effectiveness of zakat management within the educational sector plays a crucial role in improving mustahik welfare. This study aims to analyze the management of zakat by the School Zakat Management Unit (UPZ) at SMKN Pringkuku Pacitan in enhancing the well-being of its beneficiaries. Utilizing a descriptive qualitative approach, data were gathered through interviews, direct observations, and documentary reviews. The findings reveal that the zakat management mechanism has been structured systematically, encompassing collection, distribution, and mustahik classification based on the eight categories of asnaf. Specifically, professional zakat (zakat profesi) is collected via a 2.5% monthly salary deduction from civil servant (PNS) and government employee (PPPK) staff, while zakat fitrah is accumulated from all teachers, staff, and students. The allocated zakat funds are regularly distributed to underprivileged students, orphans, and the community residing around the school environment. This financial intervention is proven to yield a positive impact by supporting educational expenses, fulfilling daily basic needs, and boosting students' learning motivation. The implication of this study emphasizes that the school-based zakat management model holds significant potential to be replicated as an effective social empowerment instrument to secure student welfare.

This research is designed to portray the use of YouTube as an instructional medium, measure student learning outcomes before and after its implementation, and examine how YouTube media impacts the academic performance of fourth-grade students at SDN Socah 1. The study employed a pre-experimental design with a one-group pretest-posttest pattern. A total of 22 fourth-grade students at SDN Socah 1 were designated as research participants through purposive sampling. A written multiple-choice test consisting of 10 items was used as the data collection instrument. Data were analyzed using the normalized N-Gain formula and the Paired Sample T-Test at a significance threshold of α = 0.05. Findings showed a rise in the students' mean score from 40.9 on the pretest to 78.6 on the posttest, producing an average N-Gain of 0.67, which is classified as moderate. The Paired Sample T-Test produced a t-count of 8.751 with a significance value of 0.000 < 0.05, resulting in the rejection of H₀ and confirming that YouTube media exerted a meaningful and constructive effect on students' learning achievement. Therefore, YouTube media is worthy of consideration as an innovative and effective digital technology-based instructional alternative for fostering comprehension and academic performance among elementary school students.

This study investigates the implementation of the Gradient Boosting Machine (GBM) algorithm for network intrusion detection using the CICIDS2017 dataset within the CRISP-DM framework. The process encompasses Business Understanding, Data Understanding, and Data Preparation including data cleaning, categorical feature encoding, normalization, and data split (80 % training, 20 % testing). In the Modeling phase, GBM Hyperparameters (learning_rate = 0.1; max_depth = 5; n_estimators = 150) were optimized via Grid Search with 2-fold Cross Validation, and F1-Score  was selected as the primary metric due to class imbalance. Evaluation on the test set yielded accuracy of 99.99 %, precision of 100 %, Recall of 99.98 %, and F1-Score  of 99.99 %, demonstrating exceptional detection capability with minimal false negatives and false positives. Compared to previous studies, this GBM model outperforms in accuracy and stability without overfitting. These findings confirm GBM’s effectiveness for modern Intrusion Detection Systems and its suitability for Deployment in resource-constrained operational environments.

Malware represents an evolving cybersecurity threat that demands more effective detection methods. Conventional signature-based detection systems have limitations in identifying new variants, driving the development of deep learning-based approaches. This research implements and evaluates four variants of the YOLOv11 algorithm (n, s, m, l) for malware classification based on visual image representation. The dataset consists of 22,056 malware and benign images, divided into 70% training, 15% validation, and 15% testing across 8 classes (adware, backdoor, benign, downloader, spyware, trojan, virus, worm). Each model was trained for 100 epochs with batch size 32 using Google Colab with GPU support. Results demonstrate that all variants achieve high accuracy (97.8%-98.1%) with YOLOv11m as the best performer (98.1%). YOLOv11n offers optimal balance between accuracy (97.9%) and efficiency (1.5M parameters, 0.3 ms/img inference) ideal for real-time applications. This research surpasses previous methods such as K-NN (97.18%) and hybrid CNN (96.55%) with superior inference speed (0.3-0.9 ms/img vs tens to hundreds of ms/img), proving the effectiveness of YOLOv11 for fast, accurate, and scalable malware detection.

Phishing is one of the most common and dangerous cyber attacks as it can trick users into providing sensitive information such as usernames, passwords, and personal data. This study aims to simulate Phishing techniques using the Zphisher tool as an educational medium to improve cybersecurity awareness. The method used is a quasi-experimental approach involving 30 participants exposed to Phishing scenarios in a controlled environment using Kali Linux. The results show that 83% of participants clicked the Phishing link and 60% entered their credentials, while 40% demonstrated awareness by avoiding further interaction. These findings indicate that cybersecurity awareness is still relatively low, but Phishing simulation is effective as an experiential learning tool.

Batik motif classification has attracted growing attention in visual computing due to its role in cultural heritage preservation, textile informatics, museum documentation, and automated cataloging. Although many studies report high classification accuracy, robustness under real-world acquisition conditions remains insufficiently understood. Batik images are frequently affected by illumination variation, blur, folds, watermark overlays, wearable deformation, scale inconsistency, and background clutter, creating challenges that extend beyond conventional image-noise assumptions. Existing studies largely focus on improving classification performance, while the interactions among acquisition variability, feature representation, evaluation practice, and deployment constraints remain fragmented. This systematic literature review addresses this gap by synthesizing batik classification research through a robustness-aware perspective. Using query expansion, backward and forward citation chaining, relevance screening, and thematic coding, 116 candidate records were identified, resulting in 50 highly relevant studies for detailed analysis. The review reveals that robustness is shaped less by denoising alone than by the combined effects of acquisition conditions, representation design, evaluation realism, and deployment context. Handcrafted descriptors remain competitive for small datasets and structured motifs due to their data efficiency and interpretability, whereas deep learning models achieve the highest reported accuracy when supported by sufficient data diversity and realistic augmentation. Hybrid representations emerge as the most consistently balanced approach, combining local texture stability with higher-level abstraction across heterogeneous acquisition settings. The review further identifies recurring robustness failure patterns, including background dependency, illumination instability, motif-scale inconsistency, wearable deformation, and source-shift vulnerability. Based on these findings, a robustness-oriented research agenda is proposed, emphasizing cross-acquisition evaluation, representation-stability analysis, batik-specific robustness benchmarks, acquisition-aware augmentation, and deployable lightweight or hybrid architectures. The study contributes a domain-specific synthesis that reframes batik motif classification from an accuracy-centric task toward a robustness-aware visual recognition problem.

Python programming has become a fundamental competence in the digital era, yet students often struggle to transform algorithmic logic into functional code. This gap between conceptual understanding and practical implementation skills requires a thorough investigation into learning challenges within the Industrial Informatics Engineering Technology (TRIN) program at Politeknik Manufaktur Bandung. Grounded in Bloom's Revised Taxonomy and Cognitive Load Theory, this descriptive quantitative study utilized a Likert-scale questionnaire and an objective comprehension test administered to 87 third-year students. Data were analyzed using descriptive statistics to map performance across three aspects: conceptual understanding, syntactic comprehension, and implementation ability. Results indicate the conceptual aspect achieved the highest average of 4.15, followed by syntax at 3.56 and implementation at 3.54, with objective test accuracy rates of 76.09%, 65.52%, and 67.36%, respectively. Major obstacles identified include difficulties with looping, debugging, and comparison operators. Therefore, enhanced structured practice and Project-Based Learning approaches are recommended to strengthen students' implementation competencies.

The curriculum is one of the important elements in education which functions as a guide for carrying out learning activities at school. The success of education really depends on the teacher's ability to understand and describe the existing curriculum system. This research aims to reveal the importance of teacher accuracy in describing the curriculum system during the learning process at SDN Sumbertlaseh 2 Sumbertlaseh Village. The method applied in this research is a qualitative descriptive approach with data collection techniques through observation, interviews and documentation. The results of the research show that teachers' accuracy in understanding and explaining the curriculum system can help the learning process take place more efficiently, increase students' understanding of the material being taught, and support the achievement of educational goals more optimally. Therefore, teachers need to improve their understanding of the structure and implementation of the curriculum so that the learning process becomes better.

This study analyzes the integration of aesthetics and ethics in cosmetology education and its implications for strengthening the professionalism of cosmetology teachers. Cosmetology is often viewed as an applied field that primarily produces visual beauty through make-up, skin care, hair care, and cosmetic services. However, professional cosmetology practice also involves moral responsibility because it deals directly with the human body, personal identity, safety, comfort, and client trust. This article uses a normative qualitative method with conceptual and philosophical approaches through library research. The analysis is organized through three dimensions of philosophy of science: ontology, epistemology, and axiology. The findings show that, ontologically, cosmetology studies beauty and the human body not merely as physical objects, but as subjects with value, dignity, and diverse meanings. Epistemologically, cosmetology knowledge is constructed through the integration of scientific theory, practical skills, professional experience, sanitation principles, occupational safety, and service standards. Axiologically, cosmetology contains ethical values that guide beauty practices so that they remain honest, safe, responsible, and respectful of human dignity. The integration of aesthetics and ethics strengthens the role of cosmetology teachers as educators, professional models, and character builders in vocational education. Therefore, cosmetology learning should not only emphasize technical competence and visual results, but also internalize ethical awareness, reflective judgment, and responsibility in every stage of professional practice.

This study was conducted to analyze the relationship between students’ critical thinking skills and mathematical problem-solving abilities through a literature review approach. The study is based on the importance of mastering higher-order thinking skills in the mathematics learning process, particularly when students are faced with complex problems related to real-life situations. The method used in this research was a literature review by examining various relevant scientific journals and academic books published between 2021 and 2026. The data analysis process was carried out through stages of identification, classification, evaluation, and synthesis of the collected sources. The findings revealed a significant and positive relationship between critical thinking skills and students’ mathematical problem-solving abilities. Critical thinking skills play an important role in helping students understand problems, process and analyze information, select appropriate solution strategies, and systematically review the results obtained. Students with strong critical thinking skills generally demonstrate more optimal mathematical problem-solving abilities. In addition, the implementation of learning models such as Problem-Based Learning and contextual approaches has been considered effective in improving both abilities. Therefore, critical thinking skills are regarded as an essential aspect that needs to be developed in mathematics learning in order to enhance students’ mathematical problem-solving abilities.

This study discusses inclusive education in Early Childhood Education from the perspective of Mel Ainscow. Inclusive education is an educational approach that provides equal learning opportunities for all children without discrimination, including those with diverse learning needs. The purpose of this study is to describe the concept of inclusive education according to Mel Ainscow and to analyze its implementation in the development of early childhood education. This research employs a qualitative approach using library research methods. The data were collected from various written sources, including books, scientific journals, research articles, and documents related to inclusive education and early childhood education. Documentation techniques were used for data collection, while the data were analyzed through content analysis. The findings reveal that according to Mel Ainscow, inclusive education is a continuous process aimed at increasing the participation of all learners and reducing barriers to learning within educational environments. In the context of early childhood education, inclusive education can be implemented through flexible learning methods, child-friendly learning environments, and active collaboration between teachers and parents in supporting children’s development. The implementation of inclusive education also contributes positively to children’s social and emotional development, as they learn to respect diversity from an early age. However, several challenges remain, including limited facilities, insufficient teacher competence, and a lack of public understanding regarding inclusive education. Therefore, collaboration among schools, families, and the government is necessary to create an inclusive, equitable, and diversity-respecting early childhood education system.

Indonesia’s Free Nutritious Meal Program (MBG) requires an efficient and adaptive supply chain system to ensure timely distribution, cost efficiency, and adequate nutritional delivery for a large number of beneficiaries. However, conventional supply chain approaches are generally static and unable to respond effectively to dynamic demand, supply uncertainty, and logistical constraints. This study proposes a Multi-Objective Reinforcement Learning (MORL) model to optimize the MBG supply chain by simultaneously considering distribution cost, delivery timeliness, service level, nutritional adequacy, and food waste reduction. The model is developed using a simulation-based environment representing real-world supply chain conditions, including demand variability, transportation limitations, and kitchen capacity constraints. The results show that the proposed approach achieves cost reductions of 15–22%, improves delivery timeliness by 18–25%, maintains a service level above 90%, increases nutritional fulfillment by 12–18%, and reduces food waste by 10–15% compared to baseline methods. Sensitivity analysis further demonstrates the robustness of the model, with minimal performance degradation under disruption scenarios. These findings indicate that Reinforcement Learning provides a scalable and adaptive solution for optimizing large-scale public food distribution systems. The proposed model contributes both theoretically by integrating multi-objective optimization within an RL framework and practically by supporting data-driven decision-making for improving the effectiveness of the MBG program in Indonesia.

Problem-solving ability is an essential skill that students need to meet the demands of both academic learning and the workforce in the 21st century. This study aims to analyze the influence of self-efficacy and interpersonal communication on the problem-solving ability of eleventh-grade students at SMKN 31 Jakarta, both partially and simultaneously. A quantitative approach was employed, with data collected through a Likert scale questionnaire. Samples were drawn using a probability sampling technique with a proportional random sampling approach. Data analysis was conducted using Structural Equation Modeling (SEM) based on Partial Least Squares (SmartPLS 4.0). The results indicate that self-efficacy has a positive and significant effect on problem-solving, with a path coefficient of 0.455, a t-statistic of 7.843, and a p-value of 0.000. Similarly, interpersonal communication has a positive and significant effect on problem-solving, with a path coefficient of 0.447, a t-statistic of 7.501, and a p-value of 0.000. Taken together, self-efficacy and interpersonal communication account for the variance in problem-solving with an R-square value of 0.416, indicating that both independent variables explain 41.6% of the variation in problem-solving ability. These findings suggest that self-efficacy and interpersonal communication play a significant role in enhancing students' problem-solving ability.

Communication is an important aspect in the development of children aged 5–6 years, especially in supporting their language and social-emotional abilities. This study aims to analyze the influence of effective communication through a play approach in early childhood based on the results of previous research. The method used in this study is a quantitative method by conducting observations, research, and observations on effective communication and a play approach in early childhood education. Data collection techniques were carried out through documentation and literature searches from journals, articles, and relevant scientific references. Data analysis techniques used quantitative descriptive analysis by comparing and summarizing the results of previous research. The results show that the play approach has a significant influence on improving children's effective communication skills, such as the courage to speak, the ability to express opinions, social interaction, cooperation, and self-confidence. In addition, play activities have been proven to be able to create a fun learning atmosphere so that children are more active in interacting with peers and teachers. Thus, the play approach can be an effective strategy in developing the communication skills of children aged 5–6 years.

This study aims to develop and evaluate the feasibility of Teknoran, a website-based digital learning medium developed through the Canva application for the Office Technology subject in Grade X at SMKN 31 Jakarta. The study was motivated by learning activities that were still dominated by lecture methods and limited learning media. Teknoran was designed to facilitate learning through integrated features such as learning materials, assignments, and educational games within a single platform. This research employed the Research and Development (R&D) method using the ADDIE model, which consists of analysis, design, development, implementation, and evaluation stages. Data were collected through observation, needs analysis questionnaires, validation sheets from material and media experts, and student response questionnaires during one-to-one and small group trials. Data were analyzed using descriptive quantitative and qualitative techniques. The results showed that the Teknoran website achieved a feasibility score of 95% from material experts and 93.33% from media experts, both categorized as “Very Feasible.” Student responses also indicated a very high level of acceptance, with an average score of 95.68%. These findings demonstrate that Teknoran is highly feasible as a digital learning medium and can support more interactive, flexible, and independent learning in Office Technology subjects at SMKN 31 Jakarta.

In the Education 4.0 era, schools face unprecedented challenges in managing teacher performance effectively. Traditional top-down performance management systems have proven inadequate for fostering continuous professional growth, intrinsic motivation, and adaptive teaching competencies required in increasingly technology-driven learning environments. This study aims to develop, validate, and assess the effectiveness of a School-Based Performance Management (SBPM) model designed to enhance teacher effectiveness across cognitive, affective, and pedagogical dimensions. Using a Research and Development (R&D) design following the ADDIE framework, the study was conducted in three phases: needs analysis, model development, and model validation. Participants included 12 school principals, 186 teachers, and 8 education experts from 24 public secondary schools in [Province, Country]. Validation by experts yielded a content validity index (CVI) of 0.91. Implementation resulted in statistically significant improvements in teacher effectiveness scores (t = 8.74, p < 0.001, Cohen's d = 1.23), digital pedagogy competency (mean increase = 22.4%), and student learning outcomes (mean improvement = 17.8%). The SBPM model provides a contextually responsive, evidence-based framework that empowers schools to manage teacher performance collaboratively, fostering professional accountability and sustainable instructional quality in Education 4.0.

Students’ low critical thinking skills in mathematics remain a persistent issue, largely due to teacher-centered instructional practices that limit student participation and hinder deep conceptual understanding. To address this problem, a more engaging learning approach is required, such as the Student Teams Achievement Divisions (STAD) cooperative learning model. This study aims to examine whether students taught using the STAD model demonstrate higher critical thinking abilities than those taught through direct instruction in social arithmetic topics. The research employed an experimental method with a quantitative approach, using a posttest-only control group design. The sample consisted of two classes: an experimental group and a control group. Data were collected through essay-based tests designed to measure students’ critical thinking skills. The analysis involved prerequisite testing and hypothesis testing using an independent sample t-test. The findings revealed that the calculated t-value (2.033) exceeded the t-table value (2.00958) at a 0.05 significance level, indicating a significant difference. Therefore, the STAD model proves more effective in enhancing students’ critical thinking skills.

This study aims to map the trends, integration forms, effectiveness, and contribution of ethnomathematics in elementary school mathematics learning toward national cultural preservation. A systematic literature review (SLR) approach following the PRISMA 2020 protocol was employed. Searches across four academic databases (Scopus, Google Scholar, CrossRef, and Semantic Scholar) yielded 1,176 articles, from which 30 articles met the inclusion criteria. Results indicate that ethnomathematics research in elementary schools has increased significantly during 2023–2026, particularly following the implementation of Kurikulum Merdeka. The three most dominant forms of integration are digital modules and media (53.3%), traditional games (33.3%), and ethnomathematics-based worksheets (13.3%). Geometry and measurement is the most researched mathematics topic (50.0%), and conceptual understanding shows the most significant improvement (40.0%). Beyond improving mathematics achievement, ethnomathematics integration contributes to cultural preservation through cultural contextualization in learning (60.0%), strengthening cultural identity and values (26.7%), and active local cultural preservation (10.0%). The study recommends teacher training, curriculum policy strengthening, cross-sector collaboration, and further research to sustain ethnomathematics implementation in Indonesian elementary schools.

Dredger operations in water-based mining areas have a high occupational risk because they involve a combination of wet environments, mechanical equipment, and electrical systems. The presence of electrical panels, power cables, terminal connections, electric motors, inverters/drives, and protection components on the Dredger requires a sound understanding of Occupational Health and Safety, particularly electrical safety. Water splashes, wet walking surfaces, high humidity, and improper procedures during inspection or cleaning may increase the risk of short circuits, protection trips, and electric shock. Therefore, structured basic safety training is required so that operators are able to identify electrical hazards and implement safe working procedures. This activity aimed to improve operators’ understanding of hazardous electrical components, initial safety briefing procedures, measurement practice and safe handling during trips or short-circuit indications, and the correct and safe use of water pumps for unit cleaning. The activity was carried out through field observation, technical briefing, direct demonstration on the electrical panel and work area, simple measurement practice, and safe cleaning practice. The results indicate that field documentation can serve as an effective learning medium to strengthen operators’ understanding of electrical hazard sources on the Dredger, the application of simple lock out-tag out procedures, the control of wet areas, and the limitation of water spray direction during cleaning activities. Overall, the activity shows that improved compliance with safety procedures may reduce the risk of short circuits and electric shock during operation and maintenance.