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Journal of Electrical Engineering and Informatics
Published by Universitas Negeri Makassar
ISSN : -     EISSN : 3025213X     DOI : 10.59562
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Journal of Electrical Engineering and Informatics is a scientific journal managed by a peer review process. The Journal of Electrical Engineering and Informatics is published by the Department of Electrical Engineering Education, Universitas Negeri Makassar. The Journal of Electrical Engineering and Informatics publishes research papers and literature reviews in the fields of Electrical Engineering, Informatics and Computer Engineering, and Control.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 46 Documents
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Analysis of the Effects of Interactive Multimedia, Student Perception, and Class Participation on the Improvement of Learning Outcomes in Online Learning Labusab Labusab
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12648

Abstract

This study aims to analyze the effects of interactive multimedia, student perception, and class participation on the improvement of learning outcomes in online higher education. The focus is on students at Universitas Negeri Makassar, examining how these three factors collectively and individually influence academic achievement in a fully online learning environment. A quantitative approach was employed using a survey method. The population consisted of active undergraduate students enrolled in online courses, with 150 respondents selected through purposive sampling. Data were collected via validated questionnaires measuring the frequency and quality of multimedia use, students’ perceptions of online learning, class participation, and academic achievement. Descriptive statistics summarized the data, while multiple regression analysis was used to test the significance and magnitude of the relationships among variables. The findings indicate that interactive multimedia (β = 0.35, p < .001), student perception (β = 0.28, p < .001), and class participation (β = 0.30, p < .001) each positively and significantly affect learning outcomes. Collectively, these variables explain 63% of the variance in academic achievement, demonstrating that all three factors are critical in enhancing students’ performance in online courses. This study provides empirical evidence on the combined effect of multimedia interactivity, student perception, and participation in improving learning outcomes in online higher education. It contributes to understanding how integrated instructional strategies can optimize digital learning, offering practical guidance for educators in Indonesian universities and similar contexts worldwide.
Application of "Automotive Painting" Job Sheet Based on Direct Instruction in the "Painting Technology" Course on Sheet Metal Media Muh. Bhilal Halim
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12678

Abstract

The Painting Technology course in the Automotive Engineering Education Study Program, Faculty of Engineering, Universitas Negeri Makassar (UNM) requires students to master practical painting skills. However, a gap between theory and practice still exists. This study applies an "Automotive Painting" job sheet based on the direct instruction (DI) model to improve practical learning outcomes on sheet metal media. A quantitative descriptive approach with a one-shot case study design was employed. The subjects were 20 students in the even semester of 2025/2026 enrolled in the Painting Technology course. The course was conducted over 16 meetings (5 theory+demonstration, 2 midterm/final exams, 8 practicum sessions using DI-based job sheets). Instruments included observation sheets, product assessment rubrics (30×40 cm sheet steel panels), student response questionnaires, and quality measurements (gloss meter, coating thickness gauge, cross-cut adhesion test). Data were analyzed descriptively. Results: The average student practicum score reached 84.6 (scale 100) with a mastery rate of 95%. The most common defects were dust nibs (40% of panels) and mild orange peel (25%), which could be corrected during the finishing stage. Final product quality showed an average gloss value of 86 GU (60°), coating thickness of 122 µm, and adhesion category 4B (ASTM D3359). Student responses to the DI-based job sheet were very positive (91% agreed that the job sheet was easy to follow). This study provides the first empirical evidence of the application of an "Automotive Painting" job sheet based on direct instruction in a painting technology course at a university with a large class size in Eastern Indonesia.
Design and Development of a Phone Number–Based Anonymous Confession Application to Enhance Social Openness Hilda Ashari; Muhammad Riska
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12695

Abstract

Social openness is a fundamental aspect of interpersonal communication; however, many individuals still struggle to express their thoughts and emotions due to social pressure and fear of negative judgment. This study aims to design and develop a phone number–based anonymous confession application as an alternative communication medium to enhance users’ social openness. The research adopts a Research and Development (R&D) approach using the Waterfall model, which includes requirement analysis, system design, implementation, testing, and maintenance. The application is developed using PHP and MySQL and evaluated based on the DeLone and McLean Information System Success Model, encompassing six dimensions, system quality, information quality, service quality, use/intention to use, user satisfaction, and net benefits. The study involves two system experts as validators and fifteen university students as respondents. The evaluation results indicate that the proposed application achieved an overall score of 94.31%, categorized as excellent. Specifically, system quality scored 95.56%, information quality 94.67%, service quality 95.11%, use/intention to use 92.67%, user satisfaction 92.67%, and net benefits 94.00%. These findings demonstrate that the application provides stable performance, relevant information, and responsive services. Furthermore, high levels of user engagement and satisfaction suggest that the system is user-friendly and effective in facilitating anonymous communication. In terms of impact, the application significantly improves communication comfort and promotes greater social openness. Therefore, the developed phone number–based anonymous confession application is considered a secure, effective, and practical alternative communication platform to support social openness in the digital era.
Continuous-Time Transient Stability Assessment of Inverter-Dominated Microgrids viaPhysics-Informed Neural ODEs Andi Nur Faisal
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12701

Abstract

Objective: Inverter-dominated microgrids exhibit low rotational inertia and fast electro-magnetic dynamics, making transient stability assessment significantly more challenging than in synchronous-machine-dominated systems. This paper pro-poses a Physics-Informed Neural ODE (PI-NODE) framework that models post-disturbance inverter dynamics in continuous time, embedding the governing ODE as a hybrid of known droop-controlled inverter physics and a learned neural correction solved forward by an adaptive-step Dormand-Prince integrator. Gradients are propagated through the solver via the continuous adjoint method, keeping memory cost constant with respect to integration depth. A total of 1200 disturbance scenarios were generated from reduced-order time-domain simulations of droop-controlled grid-forming inverter microgrids with randomized virtual inertia, droop damping, fault severity, clearing time, and stochastic renewable fluctuations. On the held-out test set (180 scenarios), PI-NODE achieved 95.56% accuracy, 98.67% precision, 96.10% recall, and 97.37% F1-score for transient stability classification, with CCT MAE of 55.72 ms and RMSE of 140.48 ms. Compared with the discrete-time physics-informed deep learning (PIDL) baseline, PI-NODE yields higher precision (+1.27 percentage points) at the cost of lower recall (−1.30 percentage points), while CCT regression error is substantially larger, attributable to insufficient trajectory-fitting convergence under the 40-epoch Adam training configuration. Inference latency of 2.78 ms per sample (CPU-only) represents a 3.2× speedup over direct RK4 numerical simulation (8.98 ms per sample). Robustness testing under ±20% virtual inertia and droop scaling yielded 82.22% and 92.78% accuracy respectively, revealing that the current PI-NODE training configuration does not yet achieve the parametric robustness of the PIDL baseline. These findings identify the conditions under which continuous-time ODE formulation requires additional training strategies extended optimization, trajectory regularization, and boundary-aware sampling to realize its theoretical advantage over discrete-time physics penalization for microgrid transient stability assessment.
A SHAP-Guided Framework for Sensor Feature Minimization in Human Activity Recognition Andi Shridivia Nuran
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12788

Abstract

The increasing adoption of smartphone-based Human Activity Recognition (HAR) systems has led to the generation of high-dimensional sensor features that may introduce redundancy, increase computational complexity, and reduce model efficiency. Although feature selection techniques have been widely investigated, limited studies have explored explainable artificial intelligence approaches for progressive sensor feature minimization while maintaining classification stability. This study proposes a SHAP-guided framework for sensor feature minimization in HAR using the UCI Human Activity Recognition Using Smartphones dataset containing 561 extracted features from accelerometer and gyroscope signals across six human activities. The study employed a quantitative experimental approach using a Random Forest classifier combined with SHAP for feature importance analysis and ranking. Progressive feature reduction experiments were conducted using subsets of 300, 200, 100, 50, and 25 features. The results demonstrated that reducing the feature set from 561 to 100 features achieved approximately 82.17% feature reduction while maintaining competitive classification performance with only a minor decrease in accuracy from 92.50% to 91.75%. Furthermore, the SHAP-guided approach produced lower standard deviation values compared with random feature selection, indicating improved stability and reproducibility across repeated experiments. The novelty of this research lies in the integration of SHAP-based explainability with progressive sensor feature minimization and stability analysis in HAR, providing an interpretable and systematic framework for reducing sensor dimensionality while preserving reliable classification performance.
Development of a Website-Based Industrial Practice Management System Alifya NFH; Ayu Tri Wardani
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12906

Abstract

This research aims to develop an integrated website-based Industrial Practice Management System (PI) to digitize the entire PI process, improve administrative efficiency, and support monitoring and evaluation of student activities. This research uses the Research and Development method with the Waterfall software development model. The development stages include needs analysis, system design, implementation, system integration and testing with the black box method. The system developed has features of assessment, provision, PI registration, daily logbook management, seminar submission, approval process, and the appointment of supervisors in one platform. Functional testing was conducted against 90 test scenarios covering 19 functional needs. The test results show that all scenarios obtain a status of "Suitable", which indicates a 100% success rate and proves that all system functions are running according to the user's needs. The novelty of this research lies in the development of an Industrial Practice Management System that integrates the entire PI cycle, in contrast to previous research which generally only focused on part of the PI process. This system supports comprehensive management, real-time monitoring, and multi-role collaboration involving students, PI admins, supervisors, and study program heads so as to improve the effectiveness and quality of Industrial Practice management in universities.

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