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Journal of Electrical Engineering and Computer (JEECOM)
Published by Universitas Nurul Jadid
ISSN : 27150410     EISSN : 27156427     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy
Journal of Electrical Engineering and Computer (JEECOM) is published by Engineering Faculty of Nurul Jadid University, Probolinggo, East Java, Indonesia. This journal encompasses research articles, original research report, : 1) Power Systems, 2) Signal, System, and Electronics, 3) Communication Systems, 4) Information Technology, etc.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 241 Documents
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Voltage Stability Enhancement in Power Distribution Systems using an Improved Blue Monkey Optimization-Based D-SVCs Integration Approach Obeng, Abigail
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14639

Abstract

This paper presents an Improved Blue Monkey (IBM) optimization algorithm for enhancing voltage stability and reducing power losses in distribution networks through optimal placement and sizing of Distribution Static Var Compensators (D-SVCs). The IBM algorithm modifies the original Blue Monkey metaheuristic by incorporating a random inertia weight to accelerate convergence and improve exploration-exploitation balance. Benchmark function tests demonstrated the IBM’s superiority over the original BM and Particle Swarm Optimization (PSO) in solution accuracy, stability, and convergence speed. The proposed method was applied to the IEEE 33-bus system under varying load conditions, achieving optimal D-SVC placements at buses 7, 14, and 31, with reductions of 22.17% and 18.15% in active and reactive power losses, respectively, and an increase in minimum voltage from 0.9131 p.u. to 0.9590 p.u. Comparative analysis with the Modified Artificial Rabbit Optimization (MARO) method confirmed the IBM’s consistent performance advantage, including better Fast Voltage Stability Index (FVSI) values. The results validate the IBM algorithm as an effective and robust tool for reactive power compensation optimization in modern power distribution systems.
Internet-Connected Gamefowl Feed Control System with Weight Sensor Alimin, Alimin; Aqla, Kariman
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14529

Abstract

This study presents the design and implementation of an Internet of Things (IoT)–based feed control system for gamefowl (fighting chickens) to ensure consistent rations when the breeder is away. The system combines a load cell with an HX711 weight-sensor interface to measure dispensed feed, an Arduino Uno microcontroller to execute control logic, and an ESP8266 Wi-Fi module to exchange data with a cloud service. An Android application allows users to set the target feed mass in grams, start or stop dispensing, and monitor real-time weight feedback. A prototype development method was applied, covering requirement elicitation, hardware and software design, implementation, and functional testing. Performance was evaluated through 20 dispensing trials using a 10 g tolerance limit derived from breeder practice. The prototype achieved successful dosing in all trials, with measured outputs remaining within the defined tolerance and providing immediate feedback to the mobile interface. The results indicate that the proposed system can automate portioning, reduce the risk of overfeeding or underfeeding, and support remote feed management for small-scale poultry operations.
Web-Based DSS for Madrasah Teacher Performance Appraisal Roji, M. Fatkhur; Selviana, Renita; Hikmah, Nurul
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14551

Abstract

Teacher performance appraisal in Madrasah Diniyah Hidayatul Mubtadiin was previously carried out manually using spreadsheets and paper archives, leading to slow processing, input errors, and weak traceability of historical results. This study proposes and implements a web-based Decision Support System (DSS) to automate the appraisal process and support transparent ranking using the Profile Matching method. Teacher performance is assessed on five aspects pedagogic, professional, personality, discipline, and social using a 1–5 rating scale, with an ideal target profile set to 5 for all factors. For each factor, the system computes a GAP between actual and target values, converts the GAP to a weight via a predefined mapping, and aggregates scores by separating Core Factors and Secondary Factors. Aspect scores are calculated using a 60%:40% composition between core and secondary components, and overall rankings are produced through inter-aspect weighting. The DSS is developed with the Laravel MVC framework and supports three roles (admin, teacher, and principal), including principal verification and automatic generation of signed PDF reports for each appraisal period. Functional validation using black-box testing across ten key scenarios shows that all critical modules—data management, scoring input, computation, verification, ranking, and reporting—operate as expected. The proposed system reduces manual workload, accelerates semester appraisal activities, and improves auditability of appraisal decisions for madrasah management.
Drug Titration Process Control and Identification System Using IoT-Based RGB Sensors Jayati, Ari Endang; Wibowo, Fatmawati; Erlinasari, Erlinasari
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14747

Abstract

The process of determining the levels of drug raw materials using the titration method in pharmaceutical laboratories is generally still carried out manually, potentially causing inaccuracy in determining the titration endpoint. This study aims to design and implement an automatic drug titration control and identification system using an Internet of Things (IoT)-based RGB color sensor. The system is controlled by a built-in ATmega 2560 WiFi microcontroller integrated with a dosing pump as an actuator for adding titrant and a DC motor as a solution stirrer. The RGB sensor is used to detect color changes in the solution until it reaches orange as an indicator of the titration endpoint. The results of the titration process, in the form of process time and titrant volume, are sent in real-time via WhatsApp notifications. Tests were conducted on several drug raw materials, namely stearic acid, boric acid, and citric acid. The test results showed that the system was able to work as designed with titration results close to the manual method, with the highest accuracy level reaching 98.7%. This system is expected to improve the efficiency and consistency of the titration process in pharmaceutical laboratories.
Systematic Literature Review: Development of Digital Marketplace Platforms Based on Islamic Legal Principles Haryanto, Didik; Hoiri, Muhamad Nur; Suryono, Ryan Randy
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14260

Abstract

The development of digital marketplaces has transformed how people conduct economic transactions, including within the context of Islamic economics, which requires compliance with Sharia principles. Although digital technology has been widely adopted in digital marketplaces, it generally remains oriented toward efficiency and profit, and thus has not yet been fully able to implement the values of fiqh muamalah comprehensively. Therefore, this study aims to examine in depth how technology can be utilized as a normative system that supports Sharia compliance in digital marketplaces. This research employs a Systematic Literature Review (SLR) method to analyze scholarly articles related to Sharia-compliant e-commerce, digital payment systems, Islamic business ethics, and technology management. The literature was selected through stages of identification, screening, and thematic synthesis to obtain a comprehensive overview of technological solutions and the challenges of meeting Sharia requirements. The distinct contribution of this study lies in its emphasis that technology should be designed as a system embedded with specific values, rather than merely as a technically neutral tool. However, the implementation of Sharia-oriented technology still faces various challenges, such as algorithmic limitations, low levels of Sharia understanding, and the absence of integrated Sharia standards within digital regulations across different countries. This study concludes that Sharia compliance in digital marketplaces can only be achieved through an integrated approach that combines systems engineering, value-based organizational management, and the institutional implementation of Sharia regulation, so that digital transformation can align with the principles of justice, transparency, and benefit for the Muslim community within Islamic economics.
Utilizing MBTI to Enhance Career Fit for Information Technology Students Mualim, Wildan; Roji, M. Fatkhur; Astrella, Nathania Bayu
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14616

Abstract

A significant challenge faced by students in Information Technology (IT) programs is the mismatch between their personality traits and career paths. Many students struggle to determine the right career trajectory in the IT industry, often choosing based on market trends or peer influence rather than considering the alignment of their personality with job requirements. The lack of a psychometric-based counseling system to help align personality with career choices further exacerbates this issue. This study aims to explore the effectiveness of using the Myers-Briggs Type Indicator (MBTI) to align students' personalities with their career preferences. The research was conducted with a sample of 80 final-year students from the Information Technology and Systems program at Yadika Institute of Technology and Business Pasuruan. The findings revealed that the majority of students exhibited introverted personality traits, with INFP and INTP being the most common types. A statistically significant correlation was found between MBTI types and preferred career fields. For instance, students with INFP and INTP types leaned toward creative and analytical professions such as UI/UX design, software engineering, and data science, while ESTJ types favored managerial roles. Additionally, 73% of students reported high satisfaction with the career recommendations provided based on their MBTI results. This research supports the use of MBTI as an effective tool for career counseling, offering a more personalized approach to career decision-making.
Development Of An IoT-Based Irrigation Water Quality Monitoring System Using The CCME WQI Method for Agricultural Modernization
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.13750

Abstract

The degradation of irrigation water quality presents a critical challenge for sustainable agriculture, particularly under increasing hydrometeorological pressure. This study developed an Internet of Things (IoT)–based monitoring system and applied the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) to evaluate temporal variations in irrigation water quality.The system integrates pH, water temperature, total dissolved solids (TDS), and turbidity sensors with an ESP32 microcontroller, enabling real-time data transmission to a cloud-based platform. Water quality assessment was conducted from August to December using CCME WQI, with objectives defined based on national regulations and internationally recognized guidelines.The results reveal a progressive decline in irrigation water quality throughout the monitoring period. CCME WQI values decreased from 70.24 (Fair) in August to 32.28 (Poor) in December, indicating increasing frequency and severity of guideline exceedances. Turbidity was identified as the dominant contributor to water quality degradation, particularly during rainfall events, followed by episodic pH reductions and diurnal temperature variability. In contrast, TDS remained stable and consistently below threshold values.The integration of high-resolution IoT monitoring with the CCME WQI framework provides a reliable and objective approach for continuous irrigation water quality assessment. This method effectively captures temporal dynamics and supports early identification of critical degradation periods, offering a practical basis for adaptive irrigation water management.
Pattern Matching Algorithms for Optimizing the Accuracy of Optical Character Recognition in Automated Migrant Worker Registration Systems
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14487

Abstract

Manual registration processes for migrant workers present significant operational challenges, requiring 10-15 minutes per person with data error rates reaching 15%, hindering service efficiency in protection organizations. This research addresses these challenges by developing a domain-specific Optical Character Recognition (OCR) system optimized through multiple pattern matching algorithms tailored for Indonesian identity documents. Unlike general-purpose OCR approaches, the system implements six pattern variations for RT/RW field extraction and three hybrid strategies (direct, fuzzy, and contextual matching) for occupation fields, specifically designed to handle format inconsistencies in KTP and KK documents. Testing with 50 document samples achieved variable accuracy rates ranging from 75-95% across different field types, with the multiple pattern approach demonstrating 30.8% improvement over single-pattern methods for RT/RW fields and 20% improvement for occupation fields. Real-world deployment at Migrant Care Jember produced measurable operational improvements: 67% time reduction (12 to 4 minutes), 80% error reduction (15% to 3%), and threefold service capacity increase without additional personnel. The integrated confidence level system with visual indicators (green/yellow/red) enables non-technical users to identify fields requiring verification, enhancing practical usability. This study demonstrates that domain-specific pattern matching optimization can effectively bridge the gap between theoretical OCR advancements and practical implementation challenges in resource-constrained organizational settings, with direct implications for migrant worker protection services.
Web-Based Umrah Administration Information System at PT. Nur Haramain Mulia Tour
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14873

Abstract

PT. Nur Haramain Mulia Tour still handled several umrah administrative processes manually, including pilgrim registration, data retrieval, and report preparation. This condition reduced efficiency and increased the risk of data loss and service delays. This study aimed to develop a web-based umrah administration information system to improve administrative services, facilitate online registration, and support more structured data management. The system was developed using the Rapid Application Development approach, which consists of requirement planning, system design, and implementation stages. Data were collected through observation, interviews, and literature study, while the application was implemented using the Laravel framework and MySQL database. The resulting system supports major administrative functions, including registration, pilgrim data management, information access, and report generation within a centralized database environment. System evaluation was conducted using black-box testing for internal validation and questionnaire-based external testing involving administrative staff and prospective pilgrims. The external testing results showed a satisfaction score of 94%, indicating that the system was highly acceptable to users. The study concludes that the proposed web-based system improves the effectiveness and efficiency of umrah administrative services and assists both staff and pilgrims in managing registration and information processes more accurately and systematically.
Early Detection System For Shallot Diseases Using Deep Learning With Mobilenet V2 Architecture
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14236

Abstract

This study investigates the application of Artificial Intelligence, specifically Convolutional Neural Networks (CNN), to support early detection of shallot leaf diseases, namely Moler and Purple Spot, which are commonly identified through manual visual inspection and are prone to subjectivity. The MobileNetV2 architecture is employed using a transfer learning approach on a publicly available shallot leaf image dataset. The research stages include data preprocessing, image augmentation, model training with a fine-tuning strategy, and implementation within a web-based system. Experimental results on the test dataset indicate that the proposed model achieved an accuracy of 99.07%. In particular, the model demonstrated high recall in detecting Moler disease and high precision in identifying Purple Spot disease. These findings suggest that lightweight architectures such as MobileNetV2 are suitable for efficient and accurate plant disease detection with relatively low computational requirements.

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