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Enhancing the Transformation of Electrical Engineering Learning in Vocational High Schools through WOKWI Web Simulation Training in Greater Bandung Pramudita, Resa; Haritman, Erik; Rizqulloh, Muhammad Adli; Hartopo, Ibnu; Purnama, Wawan; Pawinanto, Roer Eka; Iglesias, Andre Reyvaldo
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 7, No 1 (2026): Reka Elkomika
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v7i1.20-29

Abstract

This article reports a community service program designed to address persistent constraints in Technical and Vocational Education and Training (TVET) microcontroller and IoT practicum, including limited laboratory kits, maintenance costs, and uneven access to hardware that can reduce the frequency and quality of hands-on learning. To support project-based learning and the ongoing digital transformation of electrical engineering education, the program aimed to enhance vocational electrical teachers’ competence in using a web-based simulation platform for ESP32-oriented microcontroller and IoT instruction. A one-day, hands-on workshop was developed using the GOAD (Goal–Objectives–Activities–Deliverables) framework and implemented with twenty teachers from ten vocational high schools. Activities included an introduction to WOKWI, basic C programming, microcontroller and IoT concepts, and contextual case studies such as automatic systems and flood-detection projects. Evaluation data were collected through a 12-item Likert questionnaire covering content, delivery, and practice aspects. Results showed high satisfaction, with average scores of 83.5% for content, 81.75% for delivery, and 79.25% for hands-on practice. The program indicates that WOKWI is a feasible tool to mitigate laboratory constraints and to support scalable, low-cost, and interactive IoT practicum in TVET.
Student Behavior Detection Using YOLOv10 for Classroom Engagement Analysis Resa Pramudita; Mochamad Rizal Fauzan; Ilyasa Nafan Faza; Jaja Kustija; Ibnu Hartopo; Muhammad Adli Rizqulloh
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 15 No 2: Mei 2026 (dalam proses)
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v15i2.24611

Abstract

Student engagement is a critical determinant of learning effectiveness, yet manual observation in classroom environments remains labor-intensive, subjective, and difficult to scale. This study examined a student behavior detection framework built on You Only Look Once (YOLO) version 10 or YOLOv10, the latest generation of real-time object detection models. A dataset of 2,600 annotated classroom images covering eight behavioral categories was collected under diverse conditions, including variations in lighting, camera perspectives, and occlusion. Five YOLOv10 variants (n, s, m, l, x) were trained and evaluated using precision, recall, F1 score, and mean average precision (mAP). The best-performing configuration achieved an overall mAP@0.5 of 0.821 and mAP@0.5:0.95 of 0.640, with strong performance on upright (AP = 0.967), bow head (AP = 0.958), and sleep (AP = 0.943), while more subtle behaviors such as writing (AP = 0.519) and hand-raising (AP = 0.650) proved challenging. Importantly, the system maintained real-time inference speeds ranging from 40 to 88 FPS depending on the YOLOv10 variant, when evaluated on an RTX 2060 GPU, thereby demonstrating its robustness for deployment in classroom settings. To ensure usability, the optimized YOLOv10 model was integrated into a Streamlit-based interactive dashboard, enabling educators to monitor engagement levels and respond with timely interventions. By combining state-of-the-art YOLOv10 architecture with real-time behavioral analytics, this work establishes a scalable foundation for intelligent classroom monitoring and contributes to advancing technology-enhanced education.