Implementasi Algoritma You Only Look Once (YOLOv8) untuk Mendeteksi Pelanggaran Lalu Lintas Berupa Tidak Menggunakan Helm (Studi Kasus di Jatiasih, Bekasi)
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Sep 20, 2024
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YOLO, Traffic Violation, Helmet, Automatic Detection, Driving Safety
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This research aims to implement the You Only Look Once (YOLO) algorithm in detecting traffic violations in the form of riders who do not use helmets in Jatiasih, Bekasi. The problem studied is the high number of violations in the form of riders who do not use helmets which play a vital role in protecting riders from danger. The expected solution is the development of an automatic detection system that is able to identify this offence with a high level of accuracy. The object of the research is motorcyclists in Jatiasih, Bekasi. The research method used includes applying the YOLO algorithm to video recordings from surveillance cameras at several monitoring points. Video data processing is done by a laptop and YOLO algorithm-based software. The results of this research are expected to support law enforcement efforts, increase awareness of helmet use, and improve road safety by building an automatic detection system that can identify offences such as not wearing a helmet. The results of this research will show how effective the YOLO algorithm is for spotting traffic offences.
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Poerwandono, E., & Barronzoeputra, G. Q. (2024). Implementasi Algoritma You Only Look Once (YOLOv8) untuk Mendeteksi Pelanggaran Lalu Lintas Berupa Tidak Menggunakan Helm (Studi Kasus di Jatiasih, Bekasi). Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(3), 3237-3247. https://doi.org/10.35870/jimik.v5i3.1017
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References
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Wu, W., & Lai, J. (2024). Multi camera localization handover based on YOLO object detection algorithm in complex environments. IEEE Access. DOI: 10.1109/ACCESS.2024.3357519.
Yang, Y., Miao, Z., Zhang, H., Wang, B., & Wu, L. (2024). Lightweight Attention-Guided YOLO With Level Set Layer for Landslide Detection From Optical Satellite Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2024.3351277.
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Zheng, C. (2023). Stack-YOLO: A friendly-hardware real-time object detection algorithm. IEEE Access, 11, 62522-62534. DOI: 10.1109/ACCESS.2023.3287101.
Alkentar, S. M., Alsahwa, B., Assalem, A., & Karakolla, D. (2021). Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection. Journal of Engineering, 27(8), 19-31.
Andrean, D., Unik, M., & Rizki, Y. (2023). Hotspots and Smoke Detection from Forest and Land Fires Using the YOLO Algorithm (You Only Look Once). JIM-Journal International Multidisciplinary, 1(1), 46-56. DOI: https://doi.org/10.58794/jim.v1i1.410.
Ardiansyah, M. R., Supit, Y., & Said, M. S. (2022). Sistem Visi Komputer untuk Kalkulasi Kepadatan Kendaraan Menggunakan Algoritma YOLO. Simtek: jurnal sistem informasi dan teknik komputer, 7(1), 52-59. DOI: https://doi.org/10.51876/simtek.v7i1.123.
Arifah, I. I., Fajri, F. N., & Pratamasunu, G. Q. O. (2022). Deteksi Tangan Otomatis Pada Video Percakapan Bahasa Isyarat Indonesia Menggunakan Metode YOLO Dan CNN. Journal of Applied Informatics and Computing, 6(2), 171-176.
Binuri, M. G. A., Haryanti, T., & Haq, M. A. (2022). Penerapan Algoritma YOLO v7 Sebagai Deteksi Kecelakaan Kendaraan Pada Lalu Lintas. Computing Insight: Journal of Computer Science, 4(2), 7-14.
Bochkovskiy, A., Wang, C. Y., & Liao, H. Y. M. (2020). Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934. DOI: https://doi.org/10.48550/arXiv.2004.10934.
Elgendy, M. (2020). Deep learning for vision systems. Simon and Schuster.
Goodfellow, I. (2016). Deep learning.
He, Y., Hu, J., Zeng, M., Qian, Y., & Zhang, R. (2024). DCGC-YOLO: The Efficient Dual-Channel Bottleneck Structure YOLO Detection Algorithm for Fire Detection. IEEE Access. DOI: 10.1109/ACCESS.2024.3385856.
Jupiter, F. (2023). IMPLEMENTASI ALGORITMA CNN DAN YOLO UNTUK MENDETEKSI JENIS KENDARAAN PADA JALAN RAYA.
Legaspi, K. R. B., Sison, N. W. S., & Villaverde, J. F. (2021, March). Detection and classification of whiteflies and fruit flies using YOLO. In 2021 13th International Conference on Computer and Automation Engineering (ICCAE) (pp. 1-4). IEEE. DOI: 10.1109/ICCAE51876.2021.9426129.
Lin, H., Deng, J. D., Albers, D., & Siebert, F. W. (2020). Helmet use detection of tracked motorcycles using cnn-based multi-task learning. IEEE access, 8, 162073-162084.
Liu, K. (2022). Stbi-yolo: A real-time object detection method for lung nodule recognition. IEEE Access, 10, 75385-75394. DOI: 10.1109/ACCESS.2022.3192034.
Liu, P., Xie, Z., & Li, T. (2023). UCN-YOLOv5: Traffic sign target detection algorithm based on deep learning. IEEE Access.
Mailoa, R. M., & Santoso, L. W. (2022). Deteksi Rompi dan Helm Keselamatan Menggunakan Metode YOLO dan CNN. Jurnal Infra, 10(2), 49-55.
Maleh, I. M. D., Teguh, R., Sahay, A. S., Okta, S., & Pratama, M. P. (2023). Implementasi Algoritma You Only Look Once (YOLO) Untuk Object Detection Sarang Orang Utan. Jurnal Informatika, 10(1).
Menon, A., Omman, B., & Asha, S. (2021, February). Pedestrian counting using Yolo V3. In 2021 International Conference on Innovative Trends in Information Technology (ICITIIT) (pp. 1-9). IEEE. DOI: 10.1109/ICITIIT51526.2021.9399607.
Menon, S., Geroge, A., Aswathy, N., & James, J. (2021, May). Custom Face Recognition Using YOLO. V3. In 2021 3rd International Conference on Signal Processing and Communication (ICPSC) (pp. 454-458). IEEE. DOI: 10.1109/ICSPC51351.2021.9451684.
Olsen, C. S., Thomas, A. M., Singleton, M., Gaichas, A. M., Smith, T. J., Smith, G. A., ... & Cook, L. J. (2016). Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law. Injury epidemiology, 3, 1-11.
Punn, N. S., Sonbhadra, S. K., Agarwal, S., & Rai, G. (2020). Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques. arXiv preprint arXiv:2005.01385. DOI: https://doi.org/10.48550/arXiv.2005.01385.
Qian, X., Wang, X., Yang, S., & Lei, J. (2022). LFF-YOLO: A YOLO algorithm with lightweight feature fusion network for multi-scale defect detection. IEEE Access, 10, 130339-130349. DOI: 10.1109/ACCESS.2022.3227205.
Redmon, J. (2016). You only look once: Unified, real-time object detection. In Proceedings of the IEEE conference on computer vision and pattern recognition.
Rosebrock, A. (2017). Deep learning for computer vision with python: Starter bundle. PyImageSearch.
Saputra, B. M., Ilman, M. Z., Audina, M., Jepri, M., & Rosyani, P. (2023). Sistem Pengenalan Tanda Lalu Lintas Menggunakan Algoritma YOLO. JURIHUM: Jurnal Inovasi dan Humaniora, 1(1), 161-164.
Sarosa, M., & Muna, N. (2021). Implementasi algoritma You Only Look Once (YOLO) untuk deteksi korban bencana alam. *Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)*, 8(4). https://doi.org/10.25126/jtiik.202184407.
Shi, Y., Li, X., & Chen, M. (2023). Sc-yolo: A object detection model for small traffic signs. IEEE Access, 11, 11500-11510. DOI: 10.1109/ACCESS.2023.3241234.
Susanti, L., Daulay, N. K., & Intan, B. (2023). Sistem Absensi Mahasiswa Berbasis Pengenalan Wajah Menggunakan Algoritma YOLOv5. JURIKOM (Jurnal Riset Komputer), 10(2), 640-647. DOI: http://dx.doi.org/10.30865/jurikom.v10i2.6032.
Szeliski, R. (2022). Computer vision: algorithms and applications. Springer Nature.
Wang, P., Wang, X., Liu, Y., & Song, J. (2024). Research on Road Object Detection Model Based on YOLOv4 of Autonomous Vehicle. IEEE Access. DOI: 10.1109/ACCESS.2024.3351771.
Wu, W., & Lai, J. (2024). Multi camera localization handover based on YOLO object detection algorithm in complex environments. IEEE Access. DOI: 10.1109/ACCESS.2024.3357519.
Yang, Y., Miao, Z., Zhang, H., Wang, B., & Wu, L. (2024). Lightweight Attention-Guided YOLO With Level Set Layer for Landslide Detection From Optical Satellite Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2024.3351277.
Yu, J., & Zhang, W. (2021). Face mask wearing detection algorithm based on improved YOLO-v4. Sensors, 21(9), 3263. DOI: https://doi.org/10.3390/s21093263.
Zheng, C. (2023). Stack-YOLO: A friendly-hardware real-time object detection algorithm. IEEE Access, 11, 62522-62534. DOI: 10.1109/ACCESS.2023.3287101.