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This study aims to obtain a comprehensive understanding of the Juz ‘Amma memorization strategy implemented at Madrasah Diniyah Takmiliyah Baitul Azhar, evaluate its effectiveness, and examine the assessment mechanisms applied in Qur’anic learning. The research employed a qualitative field-study approach, focusing on learning activities as the primary object of investigation. Data were collected through direct observation of the learning process, in-depth interviews with the madrasah principal and teachers (ustadz/ustadzah), and documentation analysis related to the memorization program. The data were analyzed through data reduction, data presentation, and conclusion drawing to generate accurate and in-depth findings. The results indicate that the memorization program utilizes a combination of talaqqi, takrir (repetition), sima’i, and small halaqah methods. These strategies have proven effective in improving students’ memorization abilities, as reflected in increased reading fluency, better tajwid accuracy, and the achievement of memorization targets. In addition, the madrasah implements a structured and continuous evaluation system consisting of daily assessments, weekly reviews, and final examinations for each juz. The evaluation focuses on memorization fluency, recitation accuracy, and overall memorization quality. The study concludes that integrating diverse memorization methods with systematic evaluation significantly enhances the effectiveness of Qur’an memorization learning in Islamic educational institutions.  

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

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.

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.

Digitalization in the fitness industry is increasingly essential to improve efficiency and service quality. However, many fitness centers still manage data manually, including KRESNA GYM, which faces challenges in member registration, workout scheduling, and facility information delivery. This study aims to design a web-based e-fitness application using the Laravel framework to support digital service management. The development follows the Waterfall model through stages of requirement analysis, design, implementation, testing, and evaluation. The application includes features such as a landing page, admin/member login and registration, management dashboards, workout schedules, equipment guides, and supplement listings. Black-box testing confirms that all features function as expected. This system simplifies administrative processes and enhances member experience, making it effective in supporting digital transformation at KRESNA GYM.

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 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.

Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.

Geographic tongue or benign migratory glossitis is a benign disorder of the oral mucosa that is relatively common in dental practice. This condition is characterized by erythematous areas caused by the loss of filiform papillae surrounded by irregular white borders. To understand the clinical characteristics of geographic tongue and the contributing factors involved in the development of the lesion in order to establish an appropriate diagnosis and provide adequate patient education. A 25-year-old female patient presented with complaints of patches on the tongue for approximately two months. The patient had been following an OMAD (One Meal A Day) diet for one year and reported an allergy to white rice. The patient also had a history of psoriasis. Nutritional deficiencies such as vitamin B complex, vitamin B12, folic acid, iron, and zinc may affect the integrity of the oral mucosa and disrupt the regeneration of the lingual epithelium. These conditions may lead to atrophy of the filiform papillae, resulting in the characteristic erythematous appearance of geographic tongue. In addition, immunological and inflammatory factors associated with psoriasis are also suspected to contribute to lesion development. Geographic tongue is a benign inflammatory condition with a multifactorial etiology, including nutritional deficiencies and immunological factors such as psoriasis. Evaluation of systemic conditions and nutritional status is important to support accurate diagnosis and proper patient management.

Diarrhea has the potential to cause an Extraordinary Event (KLB) and is currently a leading cause of mortality in Indonesia, especially in children. Antibiotics are necessary for diarrhea caused by bacteria, but irrational antibiotic prescribing can increase the risk of antibiotic resistance. This literature review was conducted to provide an overview of the level of rationality of antibiotic use in pediatric patients with diarrhea in several Indonesian health facilities. The literature review was conducted by reviewing articles obtained through a Google Scholar search using the keywords "rationality of antibiotic use," "diarrhea," "children," and "evaluation of antibiotic use." Articles were selected using inclusion and exclusion criteria, resulting in 10 suitable articles. The study results indicate that the evaluation methods for antibiotic use include the Gyssens criteria, World Health Organization criteria, Ministry of Health Decree Standards, the 2012 World Gastroenterology Organization Guidelines, and the Rational Drug Use Module. Commonly used evaluation parameters include appropriate indication, appropriate drug, appropriate dose, and appropriate patient. Most parameters have obtained rational results, but there are several studies that are not rational in the appropriate indication, appropriate drug, and appropriate dose categories. Variations in the results of rational antibiotic use at each health facility are influenced by patient characteristics, policies at the health care facility, and the level of compliance of health workers with therapy guidelines.

Diarrhea has the potential to cause an Extraordinary Event (KLB) and is currently a leading cause of mortality in Indonesia, especially in children. Antibiotics are necessary for diarrhea caused by bacteria, but irrational antibiotic prescribing can increase the risk of antibiotic resistance. This literature review was conducted to provide an overview of the level of rationality of antibiotic use in pediatric patients with diarrhea in several Indonesian health facilities. The literature review was conducted by reviewing articles obtained through a Google Scholar search using the keywords "rationality of antibiotic use," "diarrhea," "children," and "evaluation of antibiotic use." Articles were selected using inclusion and exclusion criteria, resulting in 10 suitable articles. The study results indicate that the evaluation methods for antibiotic use include the Gyssens criteria, World Health Organization criteria, Ministry of Health Decree Standards, the 2012 World Gastroenterology Organization Guidelines, and the Rational Drug Use Module. Commonly used evaluation parameters include appropriate indication, appropriate drug, appropriate dose, and appropriate patient. Most parameters have obtained rational results, but there are several studies that are not rational in the appropriate indication, appropriate drug, and appropriate dose categories. Variations in the results of rational antibiotic use at each health facility are influenced by patient characteristics, policies at the health care facility, and the level of compliance of health workers with therapy guidelines.

This study aims to determine the production process and the level of consumer acceptance of Bandung nagasari cake utilizing stevia as a natural sweetener and butterfly pea flower extract (Clitoria ternatea) as a natural coloring agent. The research employed a quantitative approach with an experimental method through organoleptic testing involving 20 panelists. Data collection techniques consisted of literature review, questionnaires, and organoleptic evaluation covering taste, texture, aroma, and appearance. The obtained data were analyzed using descriptive quantitative analysis with percentage calculations. The findings indicated that the Bandung nagasari formulation containing stevia and butterfly pea flower extract was more preferred than the formulation using granulated sugar. Approximately 90% of panelists preferred the taste attribute due to its healthier perception, while 80% of panelists favored the texture, aroma, and appearance attributes because of the softer texture and the attractive natural coloration produced by the butterfly pea flower extract. Furthermore, the product demonstrated a shelf life of 12 hours at room temperature and up to 3 days under refrigerated storage conditions. The study concludes that the incorporation of stevia and butterfly pea flower extract may serve as an innovative development of traditional Bandung nagasari cake without eliminating its traditional characteristics and shows favorable consumer acceptance.

Abstract: Detecting chili leaf diseases remains challenging due to the non-uniform manifestation of symptoms, local discoloration, small lesion regions, and visual similarity between disease patterns and natural leaf background variations. Although YOLO-based detectors provide favorable computational efficiency, lightweight variants often struggle to distinguish subtle lesion characteristics, while conventional attention mechanisms such as CBAM primarily rely on global feature aggregation and may overlook regional activation variability. To address these limitations, this study proposes a YOLOv9s-based detection framework integrated with a Region-Dispersion Channel Spatial Attention (RDCSA) module. The proposed module incorporates regional dispersion statistics, namely mean, standard deviation, and range, as channel descriptors to capture inter-region feature variability before applying spatial attention refinement. Experiments were conducted on the COLD dataset containing 532 original images from five chili leaf condition categories using a split-before-augmentation protocol to ensure objective evaluation. RDCSA was integrated at the P5 feature level and evaluated through attention placement analysis, component-wise ablation, sensitivity analysis, stability assessment, and comparison with modern attention mechanisms. The proposed YOLOv9s + RDCSA model achieved an mAP@50 of 0.894, mAP@50–95 of 0.773, precision of 0.858, recall of 0.861, and an F1-score of 0.859 with only a marginal increase in model parameters. The results suggest that regional dispersion-based attention improves feature discrimination while preserving computational efficiency, particularly for disease symptoms characterized by heterogeneous spatial patterns. Nevertheless, performance remains influenced by visually ambiguous symptom categories, indicating that further validation across multiple datasets and field conditions is required. Overall, the proposed RDCSA module enhances detection capability without substantially increasing computational overhead, making it a promising attention mechanism for lightweight plant disease detection systems.

 Education in vocational high schools (SMKs) requires effective data management to improve students’ academic achievement and discipline. At SMK Islam Secang, students’ academic scores and attendance data have so far functioned merely as administrative archives, making it difficult to identify patterns of student performance. This study aims to classify students based on academic achievement and discipline by applying the K-Means Clustering algorithm using RapidMiner. The data used in this study consist of scores from six subjects and attendance records of 35 students from the Light Vehicle Engineering (TKR) department over two semesters. The data were obtained from original school records, compiled using Microsoft Excel, and processed in RapidMiner. The clustering process employed four clusters for academic achievement and two clusters for discipline, with Euclidean Distance used as the similarity measure. The results show that in the first semester, students were grouped into four academic achievement clusters: high achievement (6 students), moderate achievement (7 students), potentially problematic (14 students), and problematic (8 students). In the second semester, the distribution changed to high achievement (19 students), moderate achievement (14 students), potentially problematic (4 students), and problematic (1 student). Meanwhile, student discipline was divided into two clusters: disciplined (31 students) and undisciplined (4 students). These results demonstrate that K-Means Clustering is effective in mapping student conditions, revealing patterns in academic performance and attendance, and supporting educational evaluation, learning planning, and early detection of students who require academic or disciplinary intervention. Keywords: Data Mining, K-Means Clustering, Academic Achievement, Discipline, RapidMiner, Vocational High School (SMK)

Instagram social media addiction has become an increasingly common phenomenon among university students. Excessive use of Instagram can negatively affect mental, social, and academic well-being, and may increase the risk of social anxiety. Students who experience Instagram addiction tend to have reduced direct social interaction, and fear of negative evaluation from others, which are key factors contributing to social anxiety. This study aims to determine the relationship between Instagram social media addiction and social anxiety among students. This study used a quantitative approach with a cross-sectional design. The sample consisted of 105 respondents selected using purposive sampling. The instruments used were the Instagram Addiction Scale (TIAS) and the Social Anxiety Scale for Social Media Users (SAS-SMU). Data analysis was conducted using the Chi-Square test. The results showed that most respondents had a moderate level of Instagram addiction (56.2%) and a moderate level of social anxiety (68.6%). The Chi-Square test indicated a significant relationship between Instagram addiction and social anxiety, with a p-value < 0.001 (p < 0.05). There is a significant relationship between Instagram addiction and social anxiety among students. However, the relationship is not always linear, as higher levels of addiction do not necessarily correspond to higher levels of social anxiety.

Instagram social media addiction has become an increasingly common phenomenon among university students. Excessive use of Instagram can negatively affect mental, social, and academic well-being, and may increase the risk of social anxiety. Students who experience Instagram addiction tend to have reduced direct social interaction, and fear of negative evaluation from others, which are key factors contributing to social anxiety. This study aims to determine the relationship between Instagram social media addiction and social anxiety among students. This study used a quantitative approach with a cross-sectional design. The sample consisted of 105 respondents selected using purposive sampling. The instruments used were the Instagram Addiction Scale (TIAS) and the Social Anxiety Scale for Social Media Users (SAS-SMU). Data analysis was conducted using the Chi-Square test. The results showed that most respondents had a moderate level of Instagram addiction (56.2%) and a moderate level of social anxiety (68.6%). The Chi-Square test indicated a significant relationship between Instagram addiction and social anxiety, with a p-value < 0.001 (p < 0.05). There is a significant relationship between Instagram addiction and social anxiety among students. However, the relationship is not always linear, as higher levels of addiction do not necessarily correspond to higher levels of social anxiety.

Antimicrobial resistance is a persistent threat to hospital care, particularly when empirical therapy relies on broad-spectrum antibiotics without continuous evaluation of local use and susceptibility patterns. This literature review aimed to synthesize evidence from four Indonesian hospital-based studies regarding antibiotic utilization, rationality assessment, and bacterial resistance profiles. A structured narrative review was conducted using four selected articles provided by the author. Data were extracted for study design, setting, population, antibiotic evaluation method, dominant antibiotic classes, rationality indicators, resistance profile, and stewardship implications. The four studies were descriptive and hospital-based, using retrospective records, concurrent observation, ATC/DDD with DU 90%, qualitative rationality criteria, and antibiogram data. The synthesis showed a consistent concentration of antibiotic use in broad-spectrum groups, especially third-generation cephalosporins, penicillins, quinolones, and macrolides. In a Bandung public hospital, total antibiotic consumption reached 95,719.01 DDD, with penicillins, cephalosporins, quinolones, macrolides, and sulfonamides included in the DU 90% segment. In intensive care, ceftriaxone was the most frequently used antibiotic and most rationality indicators were appropriate, although clinically significant drug interactions were still identified. In pediatric acute respiratory infection inpatients, cefotaxime and ceftriaxone dominated empirical therapy. Resistance mapping in Denpasar highlighted relevant Gram-positive and Gram-negative pathogens and recommended antibiotics according to susceptibility levels. Overall, the reviewed evidence supports an integrated antimicrobial stewardship model combining ATC/DDD-DU 90% surveillance, qualitative rationality evaluation, antibiogram-based empirical guidance, and periodic feedback to prescribers.

This community service program addressed the limited capacity of educators to use artificial intelligence in a structured and pedagogically responsible way for textbook development. The program focused on empowering educators through NotebookLM in the Ngabuburit AI 2026 activity. Its objective was to improve participants’ understanding and practical skills in organizing sources, designing textbook structures, developing chapter content, and generating interactive learning media. The program used a participatory training approach consisting of presentation, demonstration, guided practice, discussion, and feedback-based evaluation. The results showed that participants gained a clearer understanding of AI-assisted academic writing workflows and recognized NotebookLM as a useful tool for integrating source analysis, textbook writing, and learning media preparation. The activity also fostered new awareness that artificial intelligence can strengthen, rather than replace, educators’ academic roles in producing more systematic and interactive teaching materials.

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.