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INFOKUM
Published by SEAN INSTITUTE
ISSN : 23029706     EISSN : 27224635     DOI : -
Core Subject : Science,
Computer Science & IT
The INFOKUM a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Software Engineering. Image Processing Datamining Artificial Neural Networks
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 891 Documents
 85   86   87   88   89 
Prototype of IOT Based Traffic Light Control System with Infrared Sensor Based on Vehicle Density Dina Maizana; Ronal Kristian Manurung; Moranain Mungkin
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3101

Abstract

Traffic congestion is one of the main challenges in densely populated urban areas. Conventional traffic light systems generally work based on fixed times without considering real conditions in the field. This study aims to design a prototype of an automatic traffic light control system that is able to adjust the turn-on time based on vehicle density. The system uses infrared light-based sensors to detect the number of vehicles on each Line in real-time. The detection data is processed by the ESP32 nodemcu to determine which Line gets the green light first. The system is designed to work alternately and dynamically so that all Lines get a chance, but still prioritizes the most congested Line. Test results show that this system is able to reduce vehicle queues and improve traffic flow
Impact Analysis of Business Logic Refactoring from Client-Side to Server-Side on Application Performance in Distribution Management System at PT.XYZ Susi Maria Purba; Frank Niroy Siahaan; Genesis Tombak Dapot Tua Panjaitan; Jopel Simarmata; Oloan Bonar Nainggolan
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3102

Abstract

Although implementing client-side business logic remains a common practice in mobile application development, it can introduce significant performance inefficiencies. This study analyzes the performance impact of refactoring business logic from the client-side (Flutter) to the server-side (ASP.NET Web API) in the Delete feature of the Delivery List module within a Distribution Management System (DMS) deployed at PT. XYZ. Before refactoring, the Flutter client executed N sequential API calls per operation—one call per selected item. After refactoring, all selected items are sent in a single unified API call, with the server handling all internal iteration and routing logic. Performance evaluations were conducted programmatically using code implementations within Flutter across three key metrics: total execution time, memory usage, and network payload size. Testing was performed over 10 iterations in a controlled local environment. Results demonstrate that the server-side approach decreases average execution time by approximately 17.7%, mitigates extreme memory spikes by reducing peak memory consumption by 29.3%, and shrinks the network payload size by 0.76%. This study provides quantitative evidence that migrating business logic to the server-side yields measurable and significant performance improvements in Flutter-based mobile applications.
Internal Quality Audit Information System at Saint Thomas Catholic University Fanni Maria Dortua Tampubolon; Paska Marto Hasugian
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3109

Abstract

This study aims to develop a web-based Internal Quality Audit Information System (SIAMI) at the Quality Assurance Agency of Santo Thomas Catholic University to support the implementation of Internal Quality Audits (AMI), which were previously conducted manually using separate media such as spreadsheets, email, WhatsApp, Google Drive, and printed documents. These conditions caused inefficiencies in document management, audit implementation, audit result recapitulation, and monitoring of Corrective Action Plans (RTL). The system was developed using the Rapid Application Development (RAD) method, which consists of Requirement Planning, User Design, Construction, and Cutover stages. Data were collected through interviews, documentation, and literature studies to identify system requirements based on the internal audit business process. The application was developed using PHP as the programming language and MySQL as the database management system, while Unified Modeling Language (UML) was employed for system modeling. The results show that SIAMI successfully integrates all stages of the Internal Quality Audit process, including audit instrument management, auditor assignment, evidence document submission, audit implementation, audit result recapitulation, Management Review Meetings (RTM), Corrective Action Plans (RTL), and follow-up verification within a single web-based platform. The developed system improves the effectiveness, efficiency, and accuracy of audit data management while facilitating monitoring and evaluation activities to support continuous quality improvement at Santo Thomas Catholic University.
TRAFFIC IMPACT ANALYSIS FOR THE DEVELOPMENT OF RSUD DR. SOESELO, TEGAL REGENCY Fita Ayunina Lathifah; Ismiyati Ismiyati; Mudjiastuti Handajani
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v10i5.3110

Abstract

Hospital development dr. Soeselo Tegal Regency is a hospital effort to improve health services. The operation of the hospital building development will attract and stimulate movement. This issue will affect the smooth flow of traffic when the traffic load increases. Traffic impact analysis is an attempt to minimize the problem. This study aims to measure the traffic performance of dr. Soeselo Tegal Regency currently predicts traffic performance after it operates, calculates parking space requirements and provides several traffic scenarios. The analysis method uses PTV Vissim 22 traffic simulation software for road intersections and sections with Indonesian Road Capacity Manual 1997. The analysis results show that the traffic performance of existing conditions or without hospital development on roads and crossroads is still quite good, with the DS value below 0,75. While the results of the long-term analysis for the next five years with an increase in traffic load, there will be a decrease in traffic performance on the affected roads and intersections. So, to improve traffic performance by doing several traffic scenarios using Vissim software. The best scenario is to widen the road and regulate traffic circulation by implementing one-way streets during peak hours to increase traffic performance. The need and availability of parking space have met the demand for parking with the amount of land provided by Regional General Hospital dr. Soeselo.
The Use of Instagram as a Fashion Reference for Fisip UNMUL Students on the @Natasharizkynew Account Try Desy Rahmawati; Nurliah Nurliah; Dony Kristian; Harry Isra Muhammad
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3106

Abstract

This study aims to explore the use of Instagram as a fashion reference among female students of the Faculty of Social and Political Sciences (FISIP), Universitas Mulawarman, through the Instagram account @natasharizkynew. The study employed a descriptive qualitative approach using the Uses and Gratifications theory, which focuses on four audience needs: information, personal identity, social interaction, and entertainment. Informants were selected using purposive sampling, consisting of Muslim female students who actively use Instagram, follow @natasharizkynew, and have adopted fashion references from the account in their daily lives. Data were collected through observation, semi-structured interviews, and documentation, and analyzed using the interactive model of Miles and Huberman, including data collection, data reduction, data display, and conclusion drawing. The findings reveal that the Instagram account @natasharizkynew fulfills students' information needs by providing references for modest, syar'i, and fashionable Muslim clothing suitable for campus activities. The account also contributes to strengthening personal identity by increasing self-confidence and helping students develop a style that aligns with their personality and values. In terms of social interaction, the content becomes a topic of discussion and fosters connections with others who share similar interests. Furthermore, the account provides entertainment by creating positive emotional experiences, including feelings of happiness, comfort, tranquility, and relief from boredom. Therefore, Instagram as a fashion reference serves not only as a source of information but also as a medium for shaping identity, enhancing social relationships, and supporting the emotional well-being of Muslim female students in the digital era..
Performance Analysis of the Protection and Control System of Cummins KTA19 Generator Under Operational Disturbances at 190 kVA Loading Conditions Putra Rahmadi; Moranain Mungkin; Syarifah Muthia Putri; Indri Dayana
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3112

Abstract

The 300 kVA Cummins KTA19-G3 generator set is equipped with an advanced electronic control system and protection system managed by the Engine Control Module (ECM), designed to maintain operational stability and prevent fatal damage due to abnormal conditions. This study aims to analyze the performance, response, and accuracy of both systems when the engine experiences disturbances in the form of rotation instability (hunting) and sudden stoppage (shutdown) at a load of 190 kVA (equivalent to 63.3% of maximum capacity). The methods used include measuring operating parameters, reading ECM data history using the Cummins Insite diagnostic tool, and analyzing the system's working logic. The results show that the speed control system (Electronic Governor) works as instructed but fails to stabilize the rotation due to physical obstacles in the fuel and air systems, causing a response delay of up to 1.2 seconds. In contrast, the protection system works very precisely and according to specifications, triggering engine shutdown when it detects rotation deviations exceeding the safe limit of ±6.6% and fuel pressure below the threshold of 1.0 Bar. It was concluded that the operational failure was not caused by damage to the electronic system, but rather by the limitations of the control system in dealing with mechanical disturbances, while the protection system functioned optimally as a last resort.
Implementation and Performance Evaluation of a Digital Adjustable Voltage and Current Protection System for Off-Grid Solar Photovoltaic Applications Lamhot Tua Situmorang; Moranain Mungkin; Syarifah Muthia Putri; Muhammad Fadlan Siregar
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3113

Abstract

Off-grid Solar Photovoltaic (PV) systems are widely deployed in remote and isolated areas where access to the utility grid is unavailable. However, the reliability of these systems is often compromised by electrical disturbances, including overvoltage, undervoltage, and overcurrent conditions, which may damage inverters and connected electrical loads. This study aims to design, implement, and evaluate the performance of a Digital Adjustable Voltage and Current Protectorfor enhancing the protection of off-grid PV systems. An Adjustable AC Voltage Regulator (Variac) was employed to simulate various voltage conditions under controlled laboratory experiments, while different load levels were applied to assess the system's protection capability. The evaluated parameters included input voltage, output voltage, load current, protection status, and protection response time. Experimental results demonstrate that the proposed protection system effectively disconnects the load under undervoltage conditions at 190 VAC, overvoltage conditions at 240 VAC, and overcurrent conditions exceeding 1.15 A. Furthermore, the protection device exhibits a rapid response time ranging from 0.7 to 0.9 s, ensuring prompt isolation of abnormal operating conditions. The findings indicate that the proposed digital protection system significantly improves the operational safety, reliability, and stability of off-grid PV installations. Therefore, the developed system offers a practical and cost-effective solution for protecting standalone solar power systems, particularly in rural electrification and remote energy applications.
Artificial Intelligence in Legal Decision-Making: an Islamic Law Perspective Helma Widya; Hermansyah Alam
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3114

Abstract

Artificial Intelligence (AI) has rapidly transformed legal systems by enhancing legal research, case analysis, predictive analytics, and judicial decision-support processes. Despite these advancements, the integration of AI into legal decision-making raises significant ethical, legal, and religious concerns, particularly regarding transparency, accountability, fairness, and conformity with Islamic legal principles. This study examines the application of AI in legal decision-making from the perspective of Islamic law, with particular emphasis on the principles of Maqasid al-Shariah and the objectives of justice (al-'adl), public interest (maslahah), and the prevention of harm (dar' al-mafasid). Using a qualitative normative legal research approach, this study analyzes primary Islamic legal sources, including the Qur'an, Sunnah, classical jurisprudence, contemporary fatwas, and relevant legal and technological literature. The findings indicate that AI can serve as an effective decision-support tool in legal processes by improving efficiency, consistency, and access to justice. However, AI should not replace human judicial authority because Islamic law requires moral reasoning, contextual interpretation (ijtihad), and ethical accountability, which remain exclusive human responsibilities. Furthermore, AI systems employed in legal contexts should satisfy fundamental Shariah principles, including transparency, explainability, fairness, non-discrimination, data privacy, and human oversight. Based on these findings, this study proposes an Islamic legal governance framework for AI-assisted legal decision-making that integrates technological innovation with the ethical objectives of Maqasid al-Shariah. The proposed framework contributes to the development of trustworthy, accountable, and Shariah-compliant AI systems for future legal institutions, particularly in Muslim-majority jurisdictions.
Precision Agricultural Regional Planning Based on Big Data Analytics to Support the Sustainable Development Goals (SDGS) Ruth Riah Ate Tarigan; Abdi Sugiarto
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3119

Abstract

Agricultural regional planning plays a pivotal role in ensuring food security, environmental sustainability, and balanced regional development in line with the Sustainable Development Goals (SDGs). However, conventional planning approaches often rely on fragmented datasets and static decision-making processes, limiting their ability to respond to dynamic agricultural and environmental conditions. This study proposes a Big Data Analytics-based Precision Agricultural Regional Planning framework that integrates multi-source datasets, including satellite remote sensing, climate records, soil characteristics, topography, land use, socioeconomic indicators, and Internet of Things (IoT) sensor data. The framework employs advanced machine learning algorithms, Geographic Information Systems (GIS), and spatial analytics to identify agricultural land suitability, predict crop productivity, optimize resource allocation, and assess climate-related risks. A multi-criteria decision-making (MCDM) approach is incorporated to prioritize strategic agricultural development zones based on economic, environmental, and social sustainability indicators. The proposed model is validated using regional agricultural data through predictive accuracy metrics, spatial validation, and scenario analysis. The findings demonstrate that integrating Big Data Analytics significantly improves planning precision, enhances land-use efficiency, reduces production risks, and supports evidence-based policymaking. Furthermore, the framework contributes directly to SDG 2 (Zero Hunger) by improving agricultural productivity, SDG 9 (Industry, Innovation and Infrastructure) through digital agriculture technologies, SDG 12 (Responsible Consumption and Production) via optimized resource utilization, SDG 13 (Climate Action) by strengthening climate resilience, and SDG 15 (Life on Land) through sustainable land management. This research provides a scalable and intelligent decision-support framework for policymakers, regional planners, and agricultural stakeholders seeking to implement precision agriculture strategies for sustainable regional development.
BLDC Motor Speed Control System for Drone Applications Using Tuned PID Control by Particle Swarm Optimization (PSO) Jekli Boy Nainggolan; Beni Satria; Ahmad Dani
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3120

Abstract

This study addresses the challenge of optimal speed control for Brushless DC (BLDC) motors in drone applications, where precise and responsive control is critical for stability and maneuverability. While the Proportional-Integral-Derivative (PID) controller is standard, manual tuning for dynamic drone operations is often suboptimal. This research proposes and investigates the implementation of a PID controller whose parameters are automatically tuned using the Particle Swarm Optimization (PSO) algorithm. The primary objective is to design a superior control system that enhances transient response and robustness against disturbances common in drone flight. The methodology employs a simulation-based experimental design using MATLAB/Simulink. The PSO algorithm optimizes the PID parameters (Kp, Ki, Kd) by minimizing the Integral Time Absolute Error (ITAE) as the fitness function. The performance of the PSO-tuned PID is then compared against a conventionally tuned (Ziegler-Nichols) PID controller under scenarios including step response and load disturbance. The findings demonstrate that the PSO-PID controller significantly outperforms the conventional PID, achieving a 73% reduction in overshoot (from 14.2% to 3.8%), a 25% faster settling time, and a 28.9% quicker recovery from load disturbances. Statistical t-test analysis confirms the significant superiority of the PSO-optimized system (p < 0.001). The implications of this research are substantial, offering an efficient offline tuning method that can be deployed on flight controllers to enhance drone stability, performance, and operational reliability without requiring additional real-time computational power, thereby advancing control system design for unmanned aerial vehicles.

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