Peningkatan Kompetensi Siswa SMK di Bidang Computer Vision dengan Implementasi YOLO dan Raspberry Pi 4
DOI:
https://doi.org/10.36782/ijsr.v8i01.543Keywords:
Computer Vision, Digital Literacy, Object Detection, OpenCV, Raspberry Pi 4Abstract
The rapid development of Artificial Intelligence (AI) technology up to 2025 has positioned Computer Vision (CV) as a crucial field in industrial applications, increasing the demand for competent graduates. Vocational High Schools (SMKs) are intended to prepare students for high employability; however, a situational analysis conducted at SMK Telkom Banjarbaru, South Kalimantan, Indonesia, revealed a gap in students’ understanding and practical application of CV technologies caused by limited learning resources and inadequate curriculum integration. The Community Service Program (Pengabdian kepada Masyarakat, PkM) of the Electrical Engineering Department aimed to introduce fundamental CV concepts to enhance students’ competencies and support digital literacy initiatives. The program employed a project-based training approach, combining theoretical sessions with practical demonstrations of a real-time face detection system using Raspberry Pi 4, OpenCV, and YOLO. The effectiveness of the program was evaluated through pre- and post-assessment surveys involving 30 participants (28 students and 2 supervising teachers). The results demonstrated successful implementation of an object detection system capable of detecting single and multiple faces with accuracy approaching 1.00 (100%). Survey findings indicated an increase in participants’ understanding of CV and digital literacy from 57% to 85%. Students’ comprehension of the difference between object classification and object detection improved from 64% to 89%, while their understanding of machine learning principles increased from 60% to 89%. Overall satisfaction with the program reached 89%. In conclusion, this community service program effectively bridged the competency gap and serves as a collaborative model between higher education institutions and vocational schools.
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Anwar, S., & Abdurrohman, A. (2020). Pemanfaatan teknologi internet of things untuk monitoring tambak udang vaname berbasis smartphone android menggunakan NODEMCU WEMOS D1 mini. Infotronik: Jurnal Teknologi Informasi dan Elektronika, 5(22), 77–83. https://doi.org/10.32897/infotronik.2020.5.2.484
Belani, M., & Parnami, A. (2020). Augmented reality for vocational education training in K12 classrooms. 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), 317–320. https://doi.org/10.1109/ISMAR-Adjunct51615.2020.00090
Budianto, A. G., Zulkarnain, A. F., Suryo, A. T. E., Cahyono, G. R., Rusilawati, R., Wibowo, B. S., Az-Zahra, S. F., Atmadja, F. E. D., & Najua, S. N. (2025). Pemanfaatan teknologi internet of things untuk penunjang model pembelajaran science, technology, engineering and mathematics. Indonesian Journal for Social Responsibility, 7(01), 93–105. https://doi.org/10.36782/ijsr.v7i01.412
Çela, E., Vajjhala, N. R., Eappen, P., & Vedishchev, A. (2025). Artificial intelligence in vocational education and training. In Transforming vocational education and training using AI (pp. 1–16). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-8252-3.ch001
Culic, I., Radovici, A., & Vaduva, J. A. (2019). Teaching Computer Engineering Concepts to Non-Technical Students. ELearning & Software for Education, 1, 249-254. https://doi.org/10.12753/2066-026X-19-034
Efendi, R., Ali, G., Purnomo, W. A., Iskandar, I., & Wulandari, R. A. (2023). Augmented reality based competency based learning on computer network learning in vocational education vocational school. Jurnal Penelitian Dan Pengembangan Pendidikan, 7(2), 242–253. https://doi.org/10.23887/jppp.v7i2.62263
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. The MIT Press.
Guerrero-Osuna, H. A., Nava-Pintor, J. A., Olvera-Olvera, C. A., Ibarra-Pérez, T., Carrasco-Navarro, R., & Luque-Vega, L. F. (2023). Educational mechatronics training system based on computer vision for mobile robots. Sustainability, 15(2), 1-18. https://doi.org/10.3390/su15021386
Halim, A., Gohzali, H., Pardosi, I. A., Wong, N. P., & Megawan, S. (2025). Pelatihan pengenalan pemrograman komputer pada SMA Dharma Bakti Lubuk Pakam. ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains Dan Teknologi, 4(2), 55–66. https://doi.org/10.55123/abdikan.v4i2.4963
Hasan, Y. (2025). Edukasi pemrograman Python untuk computer vision bersama SMK Taman Siswa Medan dan SMK Yapim Biru-Biru. ULEAD: Jurnal E-Pengabdian, 5(1), 39–43.
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017). ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60(6), 84–90. https://doi.org/10.1145/3065386
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
Leong, W. Y. (2025). Artificial intelligence, automation, and technical and vocational education and training: Transforming vocational training in digital era. Engineering Proceedings, 103(1), 1-8. https://doi.org/10.3390/engproc2025103009
Mechelen, M. V., Smith, R. C., Schaper, M.-M., Tamashiro, M., Bilstrup, K.-E., Lunding, M., Petersen, M. G., & Iversen, O. S. (2023). Emerging technologies in K–12 Education: A future HCI research agenda. ACM Transactions on Computer-Human Interaction, 30(1). https://doi.org/10.1145/3569897
Mulyatno, M., Pujitresnani, A., Legowo, D. K., Firman, A., & Mahendra, A. R. (2024). Pemberdayaan siswa sekolah menengah kejuruan melalui pelatihan pengenalan machine learning. Jurnal Pengabdian Masyarakat Bangsa, 1(11), 2899–2904. https://doi.org/10.59837/jpmba.v1i11.628
Nguyen, T. N. T., Lai, N. V., & Nguyen, Q. T. (2024). Artificial intelligence (AI) in education: A case study on ChatGPT’s influence on student learning behaviors. Educational Process: International Journal (EDUPIJ), 13(2), 105–121. https://doi.org/10.22521/edupij.2024.132.7
Nurhasanah, N., & Asyiah, N. (2025). Mengenal artificial intelligence dan sistem pengenalan wajah untuk edukasi siswa SMK Fajar Ciseeng. Abdi Jurnal Publikasi, 3(6), 397–402.
Pungus, S. R., Sondakh, D. E., Liem, A. T., Adam, S. I., Mambu, J. Y. Y., & Tombeng, M. T. (2025). Meningkatkan literasi AI dan kesadaran etika digital melalui edukasi interaktif bagi pelajar sekolah menengah atas. Servitium Smart Journal, 3(2), 190–196. https://doi.org/10.31154/servitium.v4i1.38
Redmon, J., & Farhadi, A. (2018). YOLOv3: An Incremental Improvement (arXiv:1804.02767). arXiv. https://doi.org/10.48550/arXiv.1804.02767
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., & Fei-Fei, L. (2015). ImageNet large scale visual recognition challenge. International Journal of Computer Vision, 115(3), 211–252. https://doi.org/10.1007/s11263-015-0816-y
Suparyati, A., Widiastuti, I., Saputro, I. N., & Pambudi, N. A. (2023). The role of artificial intelligence (AI) in vocational education. JIPTEK: Jurnal Ilmiah Pendidikan Teknik Dan Kejuruan, 17(1). 24-35. https://doi.org/10.20961/jiptek.v17i1.75995
Supriyanto, S., Joshua, Q., Abdullah, A., Tettehfio, E., & Ramdani, S. (2023). Application of augmented reality (AR) in vocational education: A systematic literature review. Jurnal Pendidikan Vokasi, 13(2), 205–213. https://doi.org/10.21831/jpv.v13i2.54280
Tjiptady, B. C., Yoto, & Marsono. (2020). Entrepreneurship development design based on teaching factory to improve the vocational education quality in Singapore and Indonesia. In 2020 4th International Conference on Vocational Education and Training (ICOVET) (pp. 130–134). https://doi.org/10.1109/ICOVET50258.2020.9230222
Wu, T.-T., Lee, H.-Y., Wang, W.-S., Lin, C.-J., & Huang, Y.-M. (2023). Leveraging computer vision for adaptive learning in STEM education: Effect of engagement and self-efficacy. International Journal of Educational Technology in Higher Education, 20(1), 1-26. https://doi.org/10.1186/s41239-023-00422-5
Wu, X. (2021). Application of artificial intelligence in modern vocational education technology. Journal of Physics: Conference Series, 1881(3), 1-6. https://doi.org/10.1088/1742-6596/1881/3/032074
Yanto, S., & Sari, P. I. (2025). The implementasi pelatihan computer vision dan (IoT) untuk meningkatkan kompetensi industri 4.0 pada siswa SMK Negeri 9 Bandar Lampung. Sarwahita, 22(01), 109–119. https://doi.org/10.21009/sarwahita.221.10
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Copyright (c) 2025 Arief Trisno Eko Suryo, Akhmad Ghiffary Budianto, Andry Fajar Zulkarnain, Gunawan Rudi Cahyono, Rusilawati, Bayu Setyo Wibowo, Marcfiliadi Ezra Nugroho, Fridho Ery Dwi Atmadja, Feby Zulviana Efendi

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