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This study aims to analyze the management of short-term debt and its impact on cash flow smoothness in Toko Madura micro, small, and medium enterprises (MSMEs) in Surabaya City. Using a qualitative descriptive approach, the research was conducted through in-depth interviews and field observations at Toko Madura Barokah located in Pasar Wonokromo. The results show that short-term debt management is characterized by flexibility and trust-based relationships between store owners and suppliers, with payment terms ranging from 10 to 14 days. Debt management is carried out adaptively according to sales fluctuations and cash flow conditions. The average ratio of short-term debt to monthly cash flow is 17.2%, indicating that the debt level remains within a safe and manageable range. However, the financial recording system remains simple and lacks separation between personal and business finances, which may cause inaccuracies in cash control. Overall, short-term debt management contributes positively to cash flow stability through trust and payment discipline. Nevertheless, improving financial literacy and implementing a more structured accounting system are necessary to support sustainable business growth and better financial decision-making.

The rapid advancement of intelligent systems has accelerated the adoption of data-driven solutions across diverse industries, creating an increasing need for models that are both efficient and privacy-preserving. While traditional centralized machine learning approaches offer strong predictive capabilities, they often struggle with challenges related to data privacy, network latency, and computational inefficiency-especially in distributed environments with heterogeneous devices. To address these limitations, recent research has explored hybrid learning frameworks that integrate federated learning, edge computing, and dynamic model optimization techniques. These hybrid approaches enable models to process and learn from data closer to the source while maintaining stringent privacy requirements by keeping raw data localized. Additionally, the incorporation of pruning strategies, adaptive model compression, or multimodal data fusion contributes to improved speed, scalability, and accuracy in real-time inference tasks. Such frameworks have demonstrated notable promise in settings characterized by high data volume, operational complexity, and the necessity for fast anomaly detection or decision-making. However, despite these advancements, several challenges remain, including synchronization delays across edge nodes, variability in hardware capabilities, and the need for more efficient aggregation algorithms. Future developments may involve leveraging next-generation pruning techniques, energy-aware edge scheduling, decentralized orchestration protocols, or the integration of digital twin technologies to further enhance performance. Overall, hybrid distributed learning frameworks represent an important evolution toward more intelligent, secure, and autonomous computational ecosystems capable of supporting the next wave of smart applications.

The development of information technology plays an important role in improving the quality of public services, including the processes of public complaints and grant submissions. Currently, these services at the Welfare Section of Situbondo Regency are still carried out manually, which often causes recurring problems such as delayed verification, lack of transparency in decision-making, and difficulties in data archiving and retrieval. These challenges not only slow down administrative processes but also reduce public trust in government services. Therefore, the design of a web-based information system is considered crucial to support the implementation of e-government and to ensure more effective, efficient, and accountable services. This study aims to design an integrated web-based information system that facilitates both public complaints and grant submissions within one platform. The research method applied is Object Oriented Analysis and Design (OOAD), which emphasizes systematic analysis and modeling using the Unified Modeling Language (UML). The analysis phase includes identifying system requirements, business process modeling, and defining functional and non-functional needs. The design phase produces various models such as business process design, input-output forms, application architecture using a three-tier structure, UML diagrams (use case, activity, class, and sequence diagrams), and database modeling. The results of this research are expected to provide a system design that improves the speed of service delivery, enhances transparency through real-time status tracking, reduces the risk of data loss by implementing digital archiving, and increases efficiency in the verification process. Overall, the proposed system design contributes to strengthening good governance practices in Situbondo Regency and serves as a reference for similar developments in other local government institutions.

This study examines the evolution of the notary supervision system in Indonesia, particularly the impact of Constitutional Court Decision No. 49/PUU-X/2012 which revoked Article 66 paragraph (1) of Law No. 30 of 2004 and the establishment of the Notary Honorary Council (MKN) through Law No. 2 of 2014. The study uses a normative juridical method with a case and statutory approach, supported by literature analysis and expert opinion. The results show that the Constitutional Court decision eliminated legal protection for notaries in facing arbitrary actions by law enforcement officers, creating inequality with other professions such as advocates and doctors. Although the Regional Supervisory Council (MPD) still exists institutionally, the authority to grant approval for summoning notaries has been lost. In response, the government established the MKN which combines elements of the Ministry of Law and Human Rights with the Indonesian Notaries Association. International comparisons show that the civil law system provides stronger protection through specialized courts, while common law does not provide a privileged position for notaries. Indonesia adopts a mixed model that provides flexibility but creates coordination complexity. The MKN plays a role in enforcing professional ethics while maintaining a balance between the protection of notaries as public officials who make authentic deeds and accountability in the judicial system, restoring the stability of legal protection that was lost after the Constitutional Court's decision.

This paper aims to explore the legal basis and ethical reasoning for the revocation of parental rights due to domestic violence by placing the child's best interests as a compass and mapping the gap between norms and judicial practices. The method used is normative-doctrinal legal research based on a literature review of the Domestic Violence Law, the Marriage Law, the Child Protection Law, selected jurisprudence, and scientific literature, analyzed qualitatively through systematic interpretation, argument construction, and linking to the facts of the impact of domestic violence on children. The results show that positive law provides a firm basis for sanctions and protections including restrictions on interaction and revocation of custody rights, but implementation is often hampered by vague evidence of psychological violence, the victim's economic dependence, and weak execution of alimony; revocation effectively breaks the cycle when accompanied by a protection order, a post-decision parenting plan, and ongoing psychosocial support. Policy implications include guidelines for proving coercive control, expanding access to timely protection orders, integrating trauma-informed services in religious courts, and a mechanism for executing alimony that does not burden victims, with schools, community health centers, and communities as early detection nodes. Ultimately, legal work and social networks converge in one simple goal: that home again means a safe place for children to return.

The rapid development of information technology has had a significant impact on various aspects of life, including the decision-making process that requires precision and objectivity. One of the problems often faced is product selection with various complex criteria, for example in selecting a quality drum. Drums as a percussion instrument have many variations in terms of sound quality, material, design, price, and durability, so a system is needed that can assist users in making a more rational choice. This study aims to develop a website-based Decision Support System (DSS) using the Weighted Product (WP) method to provide recommendations for drum selection. The WP method was chosen because it is able to perform calculations by considering the weight of each criterion so that the recommendation results are more objective. The system implementation is carried out through the design of a user-friendly web-based interface, making it easier for users to access, compare alternatives, and obtain recommendations without having to perform manual assessments that are time-consuming and potentially subjective. System testing was carried out by comparing the results of the system's recommendations with expert assessments, which obtained an accuracy level of 95%. These results indicate that the developed system has a high level of reliability and is suitable for use as an aid in decision-making in selecting quality drums. With this system, it is hoped that users, both beginners and professionals, will find it easier to choose drums that suit their needs and preferences.

This study provides an in-depth analysis of the benefits of implementing a SAP-based Enterprise Resource Planning (ERP) system for end-users at PT XY, an Indonesian airport management company. A qualitative case study approach was applied through comprehensive in-depth interviews and direct observations of accounting division staff who actively utilize the SAP Financial Accounting (FI), Controlling (CO), and Materials Management (MM) modules as part of their daily operations. The findings demonstrate that SAP implementation significantly enhances work efficiency, data accuracy, and overall operational productivity across multiple business processes. The system facilitates seamless cross-departmental integration, reduces manual errors, accelerates financial reporting, and supports real-time, data-driven decision-making. Furthermore, SAP strengthens internal coordination by providing consistent, centralized, and easily accessible information to all relevant stakeholders. Key challenges identified include limited network access, server congestion during peak hours, and difficulties with remote connections when accessing the system outside the office environment. The company addressed these issues through regular user training, provision of secure Virtual Private Network (VPN) access, expansion of server capacity, and a strategic plan to migrate to cloud-based SAP S/4HANA to improve flexibility, scalability, and long-term system reliability. The findings not only enrich the literature on ERP adoption, with practical guidance for other organizations seeking to plan, implement, and evaluate ERP systems to meet their own business needs, including effective human resource planning and change management strategies.

The Department of Education and Culture of Situbondo Regency is a government agency responsible for providing administrative services to schools within its jurisdiction. However, based on field survey results, the current system still faces significant challenges due to its lack of integration. For instance, the process of collecting physical documents and tracking application status remains inefficient, leading to various obstacles such as service delays, risks of data loss, inconvenience for applicants, and limited transparency and accountability in data management. To address these issues, this study proposes the design of a web-based school administrative service information system. The system development process employs the Structured Systems Analysis and Design Method (SSADM), which emphasizes systematic and structured procedures to ensure functionality and efficiency. The results of this study highlight the importance of adopting information technology within government institutions, particularly the Department of Education and Culture of Situbondo Regency, as a means of supporting administrative activities. The proposed web-based system is expected to streamline administrative processes, improve service delivery, and enhance transparency in managing school-related data. Moreover, by integrating digital solutions into governance, the system can contribute to strengthening the quality of education management and supporting better decision-making processes. Ultimately, the design of this information system demonstrates the potential of technology to transform public sector services and foster accountability in education governance.

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by the dengue virus and transmitted through the bite of Aedes aegypti mosquitoes. In 2023, 48 cases of DHF were reported in the Kebun Lada Public Health Center area, reflecting a high incidence rate and limited medical resources in managing the cases. This situation emphasizes the need for an alternative solution that can support a fast and accurate diagnostic process. This study aims to develop an expert system for diagnosing DHF using the Case-Based Reasoning (CBR) method. CBR functions by comparing the symptoms experienced by patients with previous cases stored in the knowledge base, thereby producing relevant diagnostic recommendations. The proposed system is implemented as a web-based application using PHP as the programming language and MySQL as the database management system. The expected outcomes of this study are to assist medical personnel in reducing diagnostic time, improving the accuracy of decision-making, and increasing the effectiveness of health services in primary healthcare facilities. In addition, the system is designed to provide wider access for the community to recognize early symptoms of DHF, which can contribute to preventive actions and reduce the risk of severe complications. Thus, the developed expert system has the potential to become a practical solution to overcome the shortage of medical personnel and enhance public health awareness.

This article examines the legal consequences of a delayed notification of a share acquisition under Indonesian competition law, focusing on the case of PT X's takeover of PT Y. The central issue is PT X's failure to report the acquisition to the Commission for the Supervision of Business Competition (KPPU) within the mandated 30-day period, as stipulated by Law Number 5 of 1999 and its implementing regulation, Government Regulation Number 57 of 2010. The notification was submitted with a significant delay of 2,023 days, a clear violation of the statutory requirements. As a result of this non-compliance, the KPPU, through its Decision No. 31/KPPU-M/2020, imposed an administrative fine on PT X amounting to   IDR 1,050,000,000.00 (one billion fifty million rupiah). Beyond the direct financial penalty, the violation led to severe indirect repercussions, including significant    reputational damage, which threatened to erode investor confidence and disrupt existing business relationships. The KPPU's firm and consistent enforcement in this case highlights the critical function of the post-merger notification system in Indonesia as a preventative mechanism to assess transactions that could lead to excessive market concentration. The decision underscores the legal principles of     transparency, fairness, and accountability that underpin Indonesian competition law. This case serves as a powerful deterrent, signaling to all business actors that non-compliance will not be tolerated. Ultimately, such rigorous enforcement is crucial for fostering a culture of legal adherence, maintaining market integrity, and building a more transparent and competitive business ecosystem that supports sustainable economic growth in Indonesia.

Business expansion is a strategic step undertaken by companies to increase profitability while broadening their market reach. Hoka Hoka Bento (HokBen) is one of the companies that consistently implements this strategy. This study aims to identify potential locations for new HokBen outlets in Depok City by utilizing Geographic Information Systems (GIS) and spatial analysis. Several parameters were considered, including proximity to commercial and entertainment centers, competitors, educational facilities, public facilities, road networks, population density, banking services, hotels, offices, residential areas, hospitals, existing stores, and places of worship. The analysis was conducted using Euclidean Distance, Buffering, Reclassification, and the Analytical Hierarchy Process (AHP) to determine the priority weights of each criterion. These weights were then integrated through the Weighted Overlay technique to produce a location suitability map. The findings reveal that the most influential factors are commercial and entertainment buildings (0.101), road networks (0.099), and educational facilities (0.092). The resulting suitability map highlights potential areas across Depok City, particularly in zones close to community activity centers. The results demonstrate that GIS-based multicriteria analysis is effective for mapping location suitability and identifying strategic zones for expansion. Therefore, this research contributes to supporting the company’s strategic decision-making through data-driven approaches while also enriching the academic field of business geography and urban planning. In addition, the outcomes can be applied as a reference model for other fast-food chains or retail industries planning spatially optimized expansion strategies in highly competitive urban environments.

Traffic violations are one of the serious problems frequently occurring in various regions, including Binjai City. Various types of violations, such as disobeying road signs and markings, incomplete vehicle documents, and violations that threaten the safety of drivers and other road users, continue to increase despite preventive and repressive efforts carried out by the authorities. This condition indicates that handling traffic violations cannot rely solely on field enforcement but also requires the support of technology capable of analyzing data more comprehensively. This study aims to predict the level of traffic violations by applying the Naïve Bayes method through data mining techniques. The dataset used consists of traffic violation records in 2023 from the Binjai City Police Department, with the main variables including violations of traffic signs and markings, document completeness, and safety-related violations. The Naïve Bayes method was selected because of its ability to perform classification with good accuracy, simplicity, and efficiency in processing large amounts of data. The implementation of this research is realized by developing a web-based application using Visual Studio Code as the development environment and MySQL as the database system. The results of this study are expected to provide structured information regarding traffic violation patterns, support authorities in making more effective decisions, and serve as an alternative solution in the prevention and handling of traffic violations in Binjai City.

Hypertension is one of the most prevalent non-communicable diseases and a major risk factor for heart disease, stroke, and kidney disorders. The high prevalence of hypertension cases in the community, particularly in the working area of Puskesmas Kota Rantau Prapat, highlights the urgent need for more effective early detection efforts to prevent severe complications in the future. However, the limited capacity of healthcare workers in utilizing data analysis technologies has resulted in hypertension risk detection being dominated by conventional methods, which are often less accurate and inefficient. To address this issue, this community service program was conducted through training on the application of the Random Forest algorithm to analyze patients’ medical history data in order to detect hypertension risks. The training method included an introduction to the fundamentals of machine learning, data pre-processing stages, implementation of the Random Forest algorithm, and interpretation of prediction results. The outcomes of the program demonstrated that healthcare workers were able to understand the use of data analysis technologies to support more accurate early detection of hypertension. Furthermore, the participants gained practical skills in utilizing medical datasets to produce predictions that can serve as a decision-support tool for preventive medical actions.Thus, this training contributed to enhancing the capacity of community healthcare workers in integrating machine learning-based technologies into preventive healthcare services. This program is expected to serve as an initial step toward developing more effective, efficient, and sustainable data-driven health systems.

Child developmental delay is a public health issue that needs to be identified early to prevent long-term impacts on children’s quality of life. In Rantau Prapat Sub-district, cases are still found among toddlers with undernutrition, incomplete immunizations, and suboptimal developmental stimulation, which may pose risks of growth and developmental delays. This study aims to apply the Naive Bayes method in identifying child developmental delays based on health data collected through medical records and questionnaires. The research method includes data collection, pre-processing (cleaning, transformation, and normalization), classification using the Naive Bayes algorithm, and model validation with the k-fold cross-validation technique. The results showed that out of 150 toddler data samples, 30.7% experienced developmental delays, with the dominant influencing factors being nutritional status and immunization completeness. The Naive Bayes algorithm achieved an accuracy rate of 87.3% with a precision of 84.1%, recall of 85.7%, and F1-score of 84.9%. These findings demonstrate that Naive Bayes can be used as a decision support system in the early identification process of child developmental delays. Therefore, the results of this study are expected to assist healthcare workers, particularly midwives, in improving the quality of early detection and delivering more targeted interventions for children in the Rantau Prapat area.

In the automotive manufacturing industry, efficiency in quality control is a crucial factor to ensure consistent product quality. Conventional Quality Assurance (QA) processes using manual record-keeping often face challenges such as delayed reporting, human errors, and difficulty in tracking historical data. This study aims to design and implement a QA performance dashboard based on digital forms at PT Dharma Polimetal, Tbk, to enhance efficiency in production quality control. The research methodology includes direct field observation, collection of production and QA data, mapping of QA process flows, interactive dashboard interface design, and system trial implementation. The designed dashboard focuses on four main aspects: QA Incoming, QC Line, QC Gate, and Customer Handling, each containing measurable performance indicators and quality parameters. Initial implementation results indicate significant improvements in QA process monitoring, faster reporting of inspection results, and easier real-time data access for both production teams and management. The system enables early detection of potential quality issues, supports rapid decision-making, and facilitates internal and external audits. Moreover, the use of digital forms within the dashboard enhances data accuracy, minimizes human error, and creates structured historical records for long-term analysis. This study provides a tangible contribution to the digitalization of QA systems, strengthening sustainable quality control practices in the automotive industry, thereby ensuring consistent productivity and product quality.

Micro, Small, and Medium Enterprises (MSMEs) have a strategic role in the Indonesian economy, but often face challenges in effective financial management. often face challenges in effective financial management. This research This study aims to analyse the application of management accounting in increasing turnover, net profit, and cash management in Labang Iced Tea Pot MSMEs in Bangkalan Regency, East Java. Bangkalan Regency, East Java. The research method used is descriptive qualitative, with data obtained through interviews, observation, and documentation. documentation. The results showed that the application of management accounting helps Labang Iced Tea Poci in determining the optimal selling price, managing cash flow, and increasing the efficiency of operational costs. cash flow, and improve operational cost efficiency. By analysing the break-even point, budget management, and recording break-even analysis, budget management, and systematic financial recording, this MSME is able to increase net profit to Rp 254,000 per day on the able to increase net profit up to IDR 254,000 per day at certain pricing strategies. pricing strategy. In addition, structured cash management allows the business to maintain liquidity and avoid deficits. maintain liquidity and avoid operational deficits. This research concluded that management accounting plays an important role in improving financial performance and support the sustainability of MSME businesses. The implementation of management accounting not only improves the efficiency of financial management, but also serves as a foundation for better strategic decision-making. the foundation for better strategic decision-making.

This study discusses the application of the K-Means Clustering algorithm in the car rental ordering system. The objective is to help group booking data based on certain patterns such as car type, booking frequency, and rental duration. The clustering results are expected to improve service efficiency and help companies better understand customer preferences. The research was conducted using historical car rental booking data from a rental company. The results show that the K-Means method can successfully cluster booking data into several useful clusters for business decision-making. This extended paper also explores theoretical concepts of clustering, related studies, limitations of the method, and potential future enhancements such as integrating predictive analytics. It highlights the importance of transforming large volumes of raw booking data into actionable business intelligence to support marketing strategies, fleet management, and customer segmentation.  

CINDI INDRIANI (2102021004) PERANCANGAN SISTEM INFORMASI PENILAIAN KINERJA KARYAWAN MENGGUNAKAN METODE  SIMPLE ADDITIVE WEIGHTING (SAW)  PADA PT DJAMBI WARAS JUJUHAN. Dengan bahasa pemograman  PHP  dan database  MySQL. Skripsi :  Program Studi S1 Sistem Informasi, Fakultas Ilmu Komputer, Universitas Dharmas Indonesia. Tahun 2025. Sistem informasi penilaian kinerja karyawan menggunakan metode  Simple Additive Weighting (SAW)  dirancang untuk membantu PT Djambi Waras Jujuhan dalam menentukan penilaian kinerja karyawan berdasarkan kriteria yang telah ditentukan. Sistem ini menggunakan bahasa pemograman  PHP dan MySQL sebagai basis data. Penelitian ini difokuskan pada karyawan bagian produksi dan non-staf, dan sistem ini dapat diakses oleh admin dan pengguna tertentu, seperti bagian kepala kantor dan staf personalia. Sistem ini dapat membantu dalam menentukan penilaian kinerja karyawan dengan lebih akurat dan efisien. Hasil penelitian menunjukkan bahwa sistem ini dapat meningkatkan kualitas penilaian kinerja karyawan. Sistem ini dapat dikembangkan lebih lanjut untuk mencakup lebih banyak kriteria penilaian dan metode penilaian lainnya. Penelitian ini dapat menjadi contoh bagi perusahaan lain yang ingin mengembangkan sistem penilaian kinerja karyawan yang lebih efektif. Kata Kunci : Sistem Informasi Penilaian Kinerja Karyawan, Metode Simple Additive Weighting (SAW),  Penilaian Kinerja Karyawan PT Djambi Waras Jujuhan.  

This study aims to design and develop an expert system to assist in diagnosing diseases in dairy cattle at Cibugary Farm using the Forward Chaining method. The background of this research lies in the limited knowledge of farmers in identifying early symptoms of diseases, which often leads to delays in medical treatment and negatively affects dairy cattle productivity. To address this issue, an expert system was designed to replicate the reasoning process of a human expert through a knowledge base containing diagnostic rules derived from observable symptoms. The Forward Chaining method was chosen because of its capability to trace facts from known symptoms toward a conclusion regarding the type of disease affecting the cattle. The system was developed by incorporating common disease symptoms, inference rules, and a decision-making mechanism that simulates expert analysis. Testing was carried out on several diagnostic scenarios to evaluate the accuracy and efficiency of the system. The results of the study indicate that the expert system can provide an initial diagnosis quickly and accurately, producing outputs consistent with expert assessments. This functionality assists farmers in making timely decisions regarding appropriate medical interventions, thereby reducing treatment delays and minimizing the risk of disease transmission within the herd. Consequently, the Forward Chaining-based expert system is expected to serve as an innovative solution to improve dairy cattle health management and support sustainable livestock productivity at Cibugary Farm.

The maintenance of non-aviation defense equipment (main weapon system) is a critical aspect in maintaining operational readiness. However, the Maintenance, Repair, and Overhaul (MRO) system in Indonesia still faces limitations due to manual reporting, inefficiency in spare parts management, and the lack of integration of the Life Cycle Cost (LCC) approach. This study aims to design and develop the Integrated Cavalry Monitoring and Maintenance System (ICMMS) based on a web application that integrates sensors, real-time data analytics, and LCC calculation. The prototyping method was used, involving design, development, integration, and testing phases on the Maung Tactical Vehicle and Anoa Armoured Personnel Carrier at PT Pindad. The results of the prototype implementation showed a significant increase in maintenance efficiency: damage reporting time decreased from ±3 hours to ±1 minute, critical component identification became 95% faster, and maintenance scheduling shifted from reactive to predictive. Additionally, the integration of the LCC algorithm allows for more accurate maintenance cost estimation, supporting technical and strategic decision-making. This study demonstrates that ICMMS based on LCC can be an innovative digital solution to enhance MRO effectiveness and operational readiness of non-aviation defense vehicles in Indonesia. It is expected that this system will improve the resilience and cost-effectiveness of managing Indonesia’s military vehicle fleet.