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This study designs and implements an up-down counter system based on an AT89C2051 microcontroller programmed in assembly using the MC-51 application. The system modifies an existing digital clock board by mapping the display selector pins, seven-segment segment pins, pushbuttons, and buzzer to the microcontroller ports. The research method consists of literature review, hardware identification, algorithm design, assembly programming, program downloading, and functional testing using a 5 V DC supply. The implementation uses a four-digit common-cathode seven-segment display and a multiplexing routine to show the counter value in real time. The functional test shows that the system can display the initial value, increase the value through the up button, and decrease the value through the down button. The display is readable during operation, and the program can run on the target circuit after being downloaded to the AT89C2051. This study confirms that assembly programming on MC-51 can be applied to implement a simple counter system on a reused digital clock circuit. The main limitations are the absence of explicit button debouncing, overflow and underflow protection, quantitative response-time measurement, and non-volatile data retention.

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.

The fiqh principle stating that a leader’s policies and actions toward the people must be based on public welfare is an Islamic legal principle emphasizing that every action and policy of a leader should be oriented toward the interests and well-being of society. This study aims to examine the meaning, normative foundations, concepts, and implementation of this principle in state governance. The research employs a library research method with a normative approach through the analysis of the Qur’an, Hadith, fiqh literature, scholarly journals, and relevant legislation. The findings indicate that this principle has a strong foundation in the Qur’an and Hadith, particularly regarding trustworthiness, justice, and the responsibility of leaders toward their people. Conceptually, this principle is closely related to the theories of maqashid al-shari’ah and siyasah shar’iyyah, which place public welfare as the primary objective of Islamic law. In practice, the principle is applied in various fields, including public administration, law and legislation, religious policies, as well as economic and fiscal policies. Its implementation can be seen in policies concerning the prohibition of interfaith marriage, marriage dispensation, marriage legalization hearings (isbat), the suspension of Hajj departures during the COVID-19 pandemic, and the management of state finances during the era of the Rightly Guided Caliphs. Therefore, this principle demonstrates that Islamic law possesses flexible and adaptive characteristics while maintaining a strong orientation toward public welfare, making it relevant to modern systems of governance.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

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.

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.

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.

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.

Online maps applications have become an essential tool for modern society in finding the fastest and most efficient routes. However, these applications often fail to detect current road conditions such as flooding, demonstrations, accidents, or public events, causing users to get stuck in problematic routes. This study aims to develop a prototype of a community-based road condition reporting system, visualized through a web-based digital map. The system allows users to directly report road conditions by providing photo evidence, descriptions, and event categories. It is also equipped with features for designing event routes such as carnivals and suggesting alternative paths based on community reports. The development process was carried out using a simulation-based approach with scenario testing that reflects real field conditions, without involving direct user data. The implementation results show that all core features work properly. The technologies used include Leaflet.js, OpenStreetMap, and the Nominatim geolocation API. This research produces an adaptive community-based GIS model that can be further developed as an intelligent navigation solution at the city scale

Sandstone aquifers in tropical sedimentary basins are major groundwater reservoirs, yet their public-health safety is often underestimated when assessment is restricted to physicochemical quality. This review addresses the persistent mismatch between chemically acceptable groundwater and microbiologically unsafe water, especially in shallow, permeable aquifers exposed to intense rainfall, pit latrines, septic systems, dumpsites, agricultural runoff, and weak wellhead protection. A structured narrative synthesis was conducted using peer-reviewed hydrogeological, hydrogeochemical, microbiological, vulnerability, and environmental health studies from Scopus, Web of Science, ScienceDirect, SpringerLink, and Google Scholar. The review focused on tropical sandstone aquifer systems in Africa, Asia, and South America. It examined lithological controls, major-ion evolution, microbial indicators, contamination pathways, WHO-based classification, Water Quality Index applications, contamination indices, multivariate statistics, GIS-based vulnerability mapping, and integrated hydro-microbial risk scoring. The synthesis shows that groundwater chemistry is governed mainly by silicate weathering, carbonate dissolution, cation exchange, shale interbeds, residence time, and anthropogenic inputs. However, chemical compliance does not confirm potable safety. Reported evidence includes TDS below 500 mg/L in chemically acceptable Nigerian basin aquifers, while all 12 shallow wells in Abeokuta tested positive for total coliform and Escherichia coli. Microbial loads increased during wet seasons, with Calabar groundwater recording total coliform increases from 76 to 468 CFU/100 mL and Salmonella/Shigella reaching 1081 CFU/100 mL. DRASTIC mapping further classified 21% of the Dahomey Basin as highly vulnerable. The review therefore proposes an integrated framework linking hydrochemistry, microbial evidence, vulnerability, GIS, and health-risk interpretation for safer, adaptive, and evidence-based groundwater governance.

This study aims to analyze the forms, patterns, and challenges of collaborative governance in the supervision of the 2024 Badung Regent and Vice Regent Election. The main issue examined is the inter-institutional relationship established by the Badung Regency Election Supervisory Agency (Bawaslu) in strengthening electoral supervision through cooperation with various stakeholders. This research employs a descriptive qualitative approach using document analysis. The primary data were derived from the Final Report on Prevention, Supervision, Participatory Supervision, and Inter-Institutional Relations of Bawaslu Badung Regency in 2024, while supporting data were obtained from the Final Report on the Handling of Violations in the 2024 Badung Regent and Vice Regent Election. The unit of analysis consists of official documents containing data on memoranda of understanding, audiences, coordination meetings, participatory supervision, and the dynamics of alleged electoral violations. The findings indicate that collaborative governance is reflected in five main dimensions: starting conditions, institutional design, facilitative leadership, collaborative process, and outcomes. Bawaslu Badung Regency’s collaboration was manifested through 16 memoranda of understanding, 9 audiences, cross-actor coordination forums, and the involvement of media, universities, civil society organizations, religious organizations, and local communities. However, this collaboration still faces challenges, including the need for technical follow-up, stronger routine communication, and systematic evaluation of cooperation. This study contributes to public administration scholarship by positioning electoral supervision as a collaborative governance practice rather than merely a technical institutional function.

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.

The modern construction industry confronts complex challenges that require the built environment to transcend mere structural compliance and actively promote psychological well-being, productivity, and human safety. This study explores the integration of color psychology as a fundamental element in the engineering of the built environment through a multidisciplinary approach encompassing Architecture, Civil Engineering (specifically Occupational Health and Safety/OHS), and Mechanical, Electrical, and Plumbing (MEP) engineering. Drawing upon a systematic literature review following the PRISMA guidelines for structured article identification and screening, and conceptual synthesis, the findings indicate that color operates as a crucial neurobiological catalyst. Within architecture, color modulates cognition, emotion, and thermal perception (examining the hue-heat hypothesis and thermal reflectance index). In civil engineering and OHS, standardized color coding elicits heuristic responses for instantaneous hazard mitigation on-site, specifically serving to minimize visual work fatigue. Furthermore, in MEP engineering, color is utilized as an ontological mapping system to navigate critical infrastructure; this is subsequently integrated with Building Information Modeling (BIM) to facilitate spatial conflict resolution. The synergy of these disciplines, further supported by Human-Centric Lighting (HCL), is proposed as a holistic framework for optimizing the building life cycle and ensuring worker safety.

This study aims to analyze the actualization of administrative service quality in managing school administration at MTs Darussalam Parigi Baru, Pondok Aren District, South Tangerang City, including service implementation, challenges encountered, and improvement efforts. This research employed a qualitative approach using a case study method through observation, interviews, and documentation involving the head of administration, administrative staff, teachers, and students. Data were analyzed through data reduction, data presentation, and conclusion drawing. The findings indicate that administrative services have been implemented reasonably well through the application of excellent service principles, including reliability, responsiveness, responsibility, and effective communication in correspondence and student administration services. However, several challenges remain, such as limited human resources, partially manual filing systems, inadequate administrative facilities, and the absence of well-established standard operating procedures (SOPs). Improvement efforts have been carried out through strengthening work coordination, enhancing staff discipline, and developing a more structured administrative system. This study concludes that the quality of administrative services plays a strategic role in supporting administrative effectiveness and improving the quality of educational services in madrasahs.

Diabetes Mellitus is a non-communicable disease with an increasing prevalence and has become a major public health concern globally and nationally. The incidence of diabetes mellitus is influenced by various individual and environmental factors. This study aimed to analyze the relationship between age, gender, and residential proximity to landfill areas and the incidence of diabetes mellitus in Bendosari District. A quantitative analytic observational design with a cross-sectional approach was employed. The study population consisted of 1,890 patient visit records recorded in the Management Information System of Bendosari Public Health Center in 2025. A total of 363 respondents were selected using proportionate stratified random sampling. Data were analyzed through univariate analysis, bivariate analysis using the Chi-Square test, and multivariate analysis using multiple logistic regression. The findings showed that age was significantly associated with diabetes mellitus incidence (p=0.000; OR=79.790; 95% CI=53.511–118.974). Gender was also significantly related to diabetes mellitus incidence (p=0.000; OR=0.298; 95% CI=0.203–0.435), indicating that females had a higher risk than males. In contrast, residential proximity to landfill areas was not significantly associated with diabetes mellitus incidence (p=0.308; OR=1.247; 95% CI=0.439–3.540). Multivariate analysis revealed that age and gender were the dominant factors influencing diabetes mellitus incidence, with the model explaining 56.1% of the variation. The study concludes that age and gender are significant determinants of diabetes mellitus incidence, whereas residential proximity to landfill areas has not been proven to significantly affect its occurrence.

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 examines the transformation of financial management through the implementation of digital accounting in PPOB (Payment Point Online Bank) businesses, which still face manual recording problems such as input errors, delayed reconciliations, and data discrepancies. The research used a descriptive qualitative method with a case study approach involving PPOB agents in Sidoarjo. Data were collected through observation, interviews, and documentation. The findings show that digital accounting significantly improves operational efficiency through automated transaction recording, real-time data integration, and faster as well as more accurate reconciliation processes. In addition, features such as automatic validation, API integration, and audit trails help minimize recording errors and maintain data consistency. The implementation of digital accounting also supports transparency and improves the quality of financial information used in decision-making. Although challenges remain regarding agents’ technological understanding and infrastructure readiness, overall implementation has provided positive impacts on financial management effectiveness and business operations in PPOB services, making processes more efficient, accurate, and reliable.

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.

The Jambi Class II Climatological Station is the agency responsible for providing climate data and information to the public and relevant agencies. In practice, the process of handling data requests is still carried out conventionally, resulting in relatively long processing times for document management, archiving, and user service. This situation has led to several challenges, such as inefficient administrative processes, a high risk of document loss, and limitations in monitoring the status of data requests. This study aims to design a web-based Data Service Information System that can support the digitalisation of climate data services at the Class II Jambi Climatology Station. The system development method used is the prototype method, as it allows the development process to be carried out in stages based on user needs. The system design was carried out using the Unified Modelling Language (UML) as a modelling tool to describe system requirements, process flows, and user interactions with the system. The design results show that the developed system is capable of facilitating the online submission of data requests, tracking the status of requests, and managing the service database in a more structured manner. The system also provides a digital archiving feature that simplifies the management and retrieval of data request documents. The implementation of this system is expected to improve the efficiency of service processes, speed up data request processing times, enhance service transparency, and support improvements in the quality of public services at the Class IV Jambi Climatological Station.