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The rapid growth of information technology has encouraged small and medium-sized food businesses to adopt digital systems in order to improve service quality and operational efficiency. Ayam Goreng Pakdhe, a local culinary business, still relies on manual ordering processes that often lead to order inaccuracies, slow service, and limited access to sales data. This study aims to design and develop a web-based ordering system for Ayam Goreng Pakdhe using the Spiral software development method, which emphasizes iterative development, risk analysis, and continuous user feedback. The research method consists of requirement analysis, system design, implementation, and evaluation carried out in repeated cycles according to the Spiral model. Data were collected through observation, interviews with business owners and employees, and analysis of existing business processes. The results show that the proposed web-based system is able to streamline the ordering process, reduce human errors, and provide real-time information on orders and sales reports. Furthermore, the iterative nature of the Spiral method allows the system to be adjusted according to user needs and potential risks identified during development. The implementation of this system is expected to enhance operational efficiency, support better decision-making, and increase customer satisfaction, thereby contributing to the digital transformation of small-scale culinary enterprises.

Diarrhea and Tuberculosis (TB) remain significant public health problems in Indonesia, including Rembang Regency. This study aims to analyze the spatial distribution and temporal changes of Diarrhea and TB cases in Rembang Regency during 2023–2024 using a Geographic Information Sistem (GIS) approach. A descriptive-analytic method was applied using secondary data, including administrative boundary shapefiles, disease case data, and health facility data at the sub-district level. Spatial processing and analysis were conducted using QGIS to produce thematic maps and compare disease distribution patterns between years. The results indicate that Diarrhea and TB cases were unevenly distributed across sub-districts and formed distinct spatial patterns. Case changes between 2023 and 2024 varied spatially, reflecting dynamic disease trends. The integration of disease maps with health facility distribution shows that areas with high case numbers were not always supported by adequate health facilities. The implementation of GIS-based maps into a web platform enhances accessibility and supports spatial-based public health decision-making.

This study aims to design a web-based information system for vehicle management and monitoring at Bengkel Merdeka Motor, which previously relied on manual recording processes. Manual data management caused several problems, including data loss, inaccurate records, difficulties in monitoring service progress, and delays in report generation. This research applies the Object-Oriented Analysis and Design (OOAD) method supported by Unified Modeling Language (UML) to analyze system requirements and design the proposed system. The research methodology includes requirements analysis, analysis of existing and proposed systems, system design, and user interface design. The proposed system integrates vehicle data management, service offers, work orders (SPK), service progress monitoring, invoice generation, and automatic monthly reporting into a single web-based platform. The results show that the designed system improves data accuracy, operational efficiency, and transparency of service information. In addition, real-time monitoring features support better coordination between administrators and mechanics. The implementation of this system is expected to enhance service quality, reduce administrative errors, and support managerial decision-making at Bengkel Merdeka Motor.

This research investigates the development of integrated operational systems connecting terminal and ship operations for docking and berthing time optimization through systematic analysis of historical data. Port efficiency depends critically on minimizing vessel turnaround time, with berth allocation, docking procedures, and cargo operations coordination determining overall port productivity and competitiveness. Through qualitative analysis involving port operators, terminal managers, ship agents, harbor masters, and operations research specialists, this study examines how historical operational data can inform intelligent coordination systems improving berthing efficiency. Results demonstrate that data-driven integration systems incorporating predictive analytics, automated scheduling, and coordinated workflows can reduce average berth turnaround time by 15-30%, improve berth utilization by 20-35%, and decrease operational conflicts by 40-60% through optimized allocation and proactive coordination. Key implementation challenges include data quality and availability, system integration complexity, organizational coordination barriers, and resistance to automated decision support. Findings reveal that historical data-based optimization represents transformative advancement from experience-based scheduling to evidence-driven operational planning supporting port efficiency enhancement, capacity maximization, and service reliability improvement. This research contributes to port operations literature by providing practical frameworks for data-driven berthing optimization applicable to diverse port operational contexts.

The rapid development of the sea transportation industry produces a massive and complex volume of transaction data, requiring strategic management to support managerial decision-making. This research aims to implement the Executive Information System on SeaPass in order to evaluate the performance of ship ticket sales. The research method uses data visualization with a two-level drill-down mechanism, which allows the presentation of information hierarchically from general summaries to specific details. The methodological stages include needs analysis, user interface (UI) design using Figma, front-end implementation with HTML, CSS, and JavaScript, database integration, and system testing through Black Box Testing. The results showed that the SIE implementation successfully integrated operational data, including schedules, ships, and manifests, into an interactive dashboard. The two-level drill-down feature provides the ability for executives to identify operational anomalies and market fluctuations in real-time. In conclusion, the system significantly enhances executive data analysis capabilities, transforming complex transaction data into accurate strategic information, thereby supporting more precise business decision-making and adaptive to the dynamics of the marine transportation market.

The growth of the digital economy has accelerated the development of online shops as part of digital MSMEs; however, this growth has not been fully supported by systematic financial management practices. This study aims to analyze financial management strategies applied by online shops in Parepare City based on four main indicators: financial planning, recording, reporting, and control. This research employed a qualitative approach within a postpositivist paradigm. Data were collected through participatory observation, semi-structured interviews, and documentation from five online shops selected using purposive sampling. Data analysis followed an interactive model consisting of data reduction, data display, and conclusion drawing, while data credibility was ensured through source and method triangulation. The findings reveal that financial management practices have been implemented by all research objects but remain at a basic level. Financial planning is primarily short-term and experience-based, financial recording is predominantly manual, financial reporting does not yet include formal profit and loss analysis, and financial control lacks measurable quantitative indicators. These results indicate that the main challenge in online shop financial management lies not in the absence of financial practices, but in the quality of implementation and the use of financial data for strategic decision-making. This study is expected to contribute empirically to the literature on digital MSME financial management and provide practical guidance for online shop owners to improve sustainable financial management practices.

This research aims to implement a Multi-Attribute Decision Making (MADM) approach using the AHP–TOPSIS method to assist PT. XYZ in selecting the most suitable intern candidate for the Social Media Specialist position. The increasing number of applicants each year makes the selection process more complex, requiring a systematic and data-driven decision support system. AHP was used to determine the priority weights of five main criteria—Interview, Experience, Portfolio, Skill, and Achievement—along with their subcriteria. All pairwise comparison matrices met the consistency requirements, indicating valid weights. The TOPSIS method was then applied to calculate the preference scores of ten candidate alternatives based on the weighted normalized decision matrix, ideal solutions, and distance measures. The results show that candidate A3 achieved the highest preference score (0.9422), followed by A7 and A8, making them the top recommended candidates. This study demonstrates that integrating AHP and TOPSIS effectively supports companies in conducting objective, efficient, and accurate recruitment decision-making processes.

This study examines the effectiveness of problem-solving skills in enhancing decision-making processes among teachers at State Junior High Schools in Jambi Province. The research was motivated by the increasing demands placed on educators to make timely, accurate, and contextually appropriate decisions in academic, administrative, and student-related matters. A quantitative approach was employed using a survey method, involving teachers from several public junior high schools across the province. Data were collected through validated questionnaires measuring levels of problem-solving competence and decision-making quality. The results indicate a significant positive relationship between problem-solving skills and decision-making effectiveness. Teachers with higher levels of analytical thinking, alternative evaluation, and solution implementation were found to make decisions more systematically, responsively, and with greater accuracy. Moreover, the findings reveal that problem-solving skills contribute not only to improving daily pedagogical decisions but also to enhancing school governance and conflict resolution. This research highlights the importance of continuous professional development programs aimed at strengthening teachers’ cognitive and strategic abilities. The study concludes that integrating structured problem-solving training into teacher development initiatives can substantially improve decision-making quality in junior high schools, ultimately supporting better educational outcomes in Jambi Province.

The criminal justice system in Indonesia is very concerned about money laundering crimes that continue to grow along with technological advances and the complexity of modern economic crimes. This study examines in depth the legal provisions related to TPPU in Indonesia, which is based on Law Number 8 of 2010 concerning the Prevention and Eradication of Money Laundering Crimes. This research aims to identify the role of prosecutors as law enforcers in applying elements of anti-trafficking at the investigation and prosecution stages, as well as to analyze various obstacles that arise in the evidentiary process in court. Using a normative juridical approach, this study utilizes literature analysis, court decision review, and evaluation of relevant legal provisions. The findings of the study show that proving preliminary crimes and the flow of funds from crimes requires public prosecutors to have a comprehensive understanding of money laundering mechanisms, including the placement, layering, and integration stages. In practice, prosecutors face various challenges, such as difficulties in tracing the origins of assets disguised through complex transactions, limited access to financial technology data, and lack of cooperation support between law enforcement and financial institutions. These obstacles often cause the proving process to be protracted and less effective. Therefore, it is necessary to increase the capacity of law enforcement officials, strengthen coordination between agencies, and use more optimal technology to support efforts to eradicate trafficking more effectively and comprehensively.

This study analyzes multi-stakeholder collaboration in innovation-based regional development planning at the Regional Development Planning Agency (Bappeda) of Sidoarjo Regency, emphasizing institutional mechanisms, data integration and digital innovation, joint financing schemes, and actor capacity and participation dynamics. The research focuses on the need to improve the effectiveness of development planning through planned, participatory, and data-driven intersectoral collaboration. Applying a qualitative case study approach, information was collected through in-depth interviews, participant observation, and analysis of planning documents. It was then analyzed using data reduction, thematic grouping, and source triangulation techniques. The research findings indicate that institutional synergy has been realized through formal forums such as development planning meetings and group discussions. However, coordination remains suboptimal due to overlapping roles between regional government agencies and the lack of a sustainable collaborative mechanism. Digital data integration still faces challenges due to limited platform content and user technical capabilities, resulting in data utilization not fully supporting evidence-based decisions. In terms of financing, collaborative schemes have begun to be implemented but are inconsistent, particularly in combining funding sources from various sectors. The capabilities of actors show striking differences, which impact the quality of public engagement and the efficiency of facilitating the planning process. Overall, these results confirm that the effectiveness of innovative planning is largely determined by the integration of digital systems, strengthening collaboration between stakeholders, and enhancing institutional capacity. This study suggests designing a more organized, interactive, and long-term multi-actor synergy model.

This study aims to develop a predictive model using linear regression to identify potential arrhythmias in the elderly based on electrocardiogram (ECG) data. Data were collected through observations at healthcare facilities from elderly patients with indications of arrhythmia, then preprocessed such as cleaning, normalization, feature selection, and outlier checking were carried out. The features used include PR interval, QRS duration, QT interval, and heart rate. The dataset was divided into training data (80%) and test data (20%) to build and evaluate the model. The training results showed that the model was able to predict the risk of arrhythmia with a Mean Squared Error (MSE) value of 0.15 and a coefficient of determination (R²) close to 1. Evaluation using a confusion matrix showed an accuracy of 76.19%, precision of 82.80%, recall of 76.19%, and F1 score of 72.70%. These results prove that linear regression can be used as an initial approach in the early detection of arrhythmias non-invasively in the elderly. This study provides a foundation for the development of ECG data-based clinical decision support systems and suggests future exploration of more complex models and integration with real-time monitoring technologies.

The Lamongan Regency Communication and Informatics Office plays a strategic role in supporting regional government decision-making through the implementation of the Megilan Innovation and Technology Program. The role of the Lamongan Regency Communication and Informatics Office in this program is realized as the main manager of digital information and archive systems that serve as the basis for providing data and information for regional leaders. Through the Megilan Innovation and Technology Program, the Communication and Informatics Office is responsible for everything from formulating archive digitization policies, implementing technology-based incoming mail management techniques, to providing fast, accurate, and integrated information to support the decision-making process. This study uses a descriptive qualitative method with interview and observation techniques carried out in the context of internship activities at the Lamongan Regency Communication and Informatics Office. Data analysis was carried out using the Miles and Huberman model which includes data collection, data condensation, data presentation, and drawing conclusions. The results of the study indicate that archive digitization through the Megilan Innovation and Technology Program can accelerate information access, improve the accuracy of letter disposition, and strengthen transparency and accountability of regional government. However, obstacles are still found in the form of limited human resources, technological infrastructure, and synchronization of physical and digital archives. Therefore, strengthening organizational capacity and supporting policies is necessary to ensure the Communication and Informatics Agency's role in decision-making can be optimal and sustainable

Selecting the right supplier is a critical aspect of supply chain management, especially in a retail business like Parfume Corner, which relies on product quality, availability, and on-time delivery. This study aims to implement the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method as a multi-criteria decision-making approach to determine the best perfume supplier. The VIKOR method was chosen because of its ability to handle conflicts between criteria and produce optimal compromise solutions. The evaluation criteria used include product quality, price, on-time delivery, after-sales service, and flexibility in negotiations. Data were collected from five potential suppliers through observation, interviews, and historical transaction documents. The analysis results showed that one supplier obtained the lowest VIKOR index score, thus being determined as the best compromise solution. The implementation of the VIKOR method proved effective in providing objective and transparent recommendations, which can support Parfume Corner's strategic decisions in building long-term partnerships with reliable suppliers. This approach can also be adapted by similar businesses to improve procurement efficiency and quality. The test results obtained were that in the expert test a Good value was obtained, namely 80%, while in the system test a Very Good conclusion was obtained, namely 100%.

This study compares the effectiveness of MAUT (Multi-Attribute Utility Theory), SMART (Simple Multi-Attribute Rating Technique), and WASPAS (Weighted Aggregated Sum Product Assessment) methods in a decision support system for determining the best employees at Sisilia Boutique. The quality of human resources is crucial in the retail business, but performance evaluation is often influenced by subjectivity. To address this, a multi-criteria-based decision support system is needed. MAUT translates preferences into a numerical scale, SMART calculates the average value of attributes based on weights, while WASPAS combines weighted summation (WSM) and weighted multiplication (WPM) for more balanced results. Employee performance data from Sisilia Boutique in June 2025, including attendance, store layout, customer service, and discipline, were used as the research object. The comparison results show consistency in the highest (K3) and lowest (K7) ratings across the three methods, with differences in the middle ratings. WASPAS offers a more balanced distribution of final scores, making it a comprehensive alternative for performance evaluation.

This study aims to analyze the strengthening of higher education governance in realizing transparent and accountable academic services. In the context of the globalization of higher education and increasing public accountability demands, universities are required not only to excel academically but also to provide services that are open, responsive, and accountable. This research employs a qualitative approach with a descriptive-analytical design. Data were collected through in-depth interviews, observations, and documentation studies involving university leaders, academic administrators, lecturers, and students. Data analysis was conducted interactively through data reduction, data display, and conclusion drawing. The results indicate that the principle of transparency has been implemented through digital-based academic information systems; however, consistency in updating information still needs improvement. Accountability has been supported by standard operating procedures and service evaluations, although performance measurement based on indicators has not been fully integrated. Stakeholder participation has been facilitated through evaluation forums, but involvement in strategic decision-making remains limited. Overall, the dimensions of transparency, accountability, participation, effectiveness, and responsibility are interrelated in shaping the quality of academic services. This study emphasizes that strengthening governance must be systemically internalized within organizational culture and institutional operational systems to enhance trust and stakeholder satisfaction.

In the era of globalization and digital transformation, organizations strive to maintain competitiveness through optimizing internal factors such as work culture, business process engineering (BPR), and decision support systems (DSS). This qualitative research based on a Systematic Literature Review (SLR) analyzes the relationship between these three using the Denison Organizational Culture Model, Hammer & Champy BPR, and the Resource-Based View (RBV). It finds that work culture mediates the implementation of BPR and DSS to increase efficiency by 30-50%, employee productivity, and sustainable competitive advantage. Case studies such as the Toyota Production System (TPS) confirm this synergy, resulting in reduced costs, cycle times, and improved service quality. This research also emphasizes the importance of a strong work culture in supporting the implementation of new technologies and methodologies, which in turn strengthens the company's market position. Thus, organizations that are able to integrate these three elements will be better prepared to face the challenges of globalization and dynamic changes in their industry, creating a sustainable advantage and being able to survive in a highly competitive market.

This research extends the previous work of Tsaqila, Winiarti, and Widaningrum (2024), who applied the Complex Proportional Assessment (COPRAS) method within a decision support system for supermarket branch location selection. Unlike the prior study, which focused on Ponorogo through a web-based framework, this study expands the implementation of COPRAS to the Medan Area, Medan Kota, Medan Polonia, dan Medan Maimun districts, adapting it to local urban, social, and economic characteristics. The main objective is to identify the most strategic site for a new supermarket by analyzing multiple criteria, including land cost, population density, accessibility, safety, cleanliness, and disaster risk. Data were collected from both field surveys and official government publications. The findings reveal that the COPRAS method provides reliable and objective assessments among the evaluated alternatives, with Medan Area emerging as the most suitable location for supermarket development. Overall, this study broadens the practical scope of the COPRAS method in a different regional context and reinforces its reliability and adaptability as a multi-criteria decision-making tool in the modern retail industry.

This article aims to provide a comprehensive literature review on how professional ethics can serve as an effective strategy to prevent fund misuse within organizational financial management. Professional ethics is viewed as a set of moral values, behavioral norms, and professional standards that guide financial managers to perform their duties with honesty, responsibility, and without conflicts of interest. In the context of financial management, these duties include recording, budgeting, monitoring, and reporting financial activities, all of which require accuracy and transparency. The study highlights five main principles of professional ethics: integrity, objectivity, professional competence, confidentiality, and professional behavior. These principles clarify rules, strengthen accountability, and ensure that financial processes comply with established standards. The literature review shows that applying professional ethics not only encourages individuals to act correctly but also enhances responsibility, improves performance, and strengthens financial oversight. Integrity and objectivity play a crucial role in preventing report manipulation, budget inflation, and fund misuse, as these principles demand moral courage and fair decision-making. Professional competence ensures that every financial process is carried out accurately and in accordance with regulations, while confidentiality protects sensitive information from misuse. Professional behavior emphasizes adherence to laws, organizational policies, and professional standards. The article also identifies several supporting factors that enable the effective implementation of professional ethics, such as strong internal policies, leadership commitment to integrity, an ethical workplace culture, layered supervision systems, and continuous ethics training. Conversely, common challenges include weak internal controls, limited understanding of ethics, organizational pressure, conflicts of interest, and inconsistent application of ethical standards. Therefore, this article underscores that integrating professional ethics into organizational financial policies, procedures, and management systems is a key step in preventing fund misuse and strengthening stakeholder trust in the organization’s transparency and accountability.

The attendance recording system at PLN ULP Tanjungbalai still relies on manual, paper-based methods, resulting in delays in data recap, reduced efficiency, and a high potential for recording errors. This condition affects the accuracy of employee attendance information, which is essential for administrative activities and managerial decision-making. Based on these issues, this practical work aims to design and develop a web-based e-attendance application as a solution to enhance efficiency, processing speed, and the accuracy of attendance recapitulation. The system was developed using PHP as the programming language and MySQL as the database management system, following several stages including requirement analysis, system design using UML, and implementation of a web-based user interface. The application provides essential features such as user login, daily attendance recording, employee data management, attendance notes (permission, sickness, etc.), and automatic attendance report generation. The system is designed for two types of users—Admin and Employees—each with specific access rights. The implementation results indicate that the e-attendance application significantly improves the efficiency of attendance administration at PLN ULP Tanjungbalai. Data collection and recapitulation become faster, more structured, and less prone to errors, while also enabling administrators to monitor employee attendance in real time. Therefore, this web-based e-attendance application serves as an effective solution to support operational activities and enhance the quality of employee attendance management.

Background: The development of industrial technology in the Industry 4.0 era has encouraged the implementation of intelligent monitoring systems to improve machine reliability and operational efficiency. However, machine fault diagnosis systems based on artificial intelligence often face limitations in terms of interpretability because the models used are complex and difficult to explain. Objective: This study aims to develop a deep learning-based industrial machine fault diagnosis system integrated with an Explainable Artificial Intelligence (XAI) approach to improve diagnostic accuracy while providing interpretable insights for users. Method: The research method involves collecting data from industrial machine sensors consisting of vibration signals, temperature measurements, and acoustic signals, followed by data preprocessing and feature extraction processes. The processed data are then used to train a deep learning-based diagnostic model, after which explainability methods such as SHAP or LIME are applied to analyze the contribution of each feature to the model’s prediction results. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results: The results indicate that the proposed deep learning model achieves better performance compared to conventional machine learning methods such as Support Vector Machine and Random Forest. Furthermore, the explainability analysis reveals that vibration amplitude, increases in machine component temperature, and anomalies in acoustic signals are the main factors influencing machine fault detection. Therefore, the proposed system not only improves the accuracy of machine fault diagnosis but also provides transparency in the decision-making process, thereby supporting the implementation of predictive maintenance in smart manufacturing environments.