Implementasi Metode YOLO pada Deteksi Pakaian Keselamatan yang Lengkap di Proyek Kontruksi
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Published
Dec 27, 2023
Abstract
Safety at work is important, so the use of personal protective equipment (ADP) is a must. However, in reality on the ground, there are relatively few workers who use complete and correct PPE. Due to this problem, the company as the person responsible employs K3 officers to monitor workers' use of PPE. To reduce the costs incurred in employing K3 officers, a system was created that was able to detect and monitor worker discipline in using PPE. Therefore, a personal protective equipment detection system was created. One method created to create object detection is the You Only Look Once (YOLO) method. The way YOLO works is by looking at the entire image once, then passing through the neural network once to directly detect existing objects. The results of this implementation aim to detect project workers who use complete protective equipment and do not use it, with the output results in the form of images that have been detected by people who use complete protective equipment or do not use it with labeling and bounding boxes on the detected image. From the test results on a total of 96 images, it shows that there is an accuracy value of 65%.
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How to Cite
Ismail Arianto, B. and zuliarso, E. (2023) “Implementasi Metode YOLO pada Deteksi Pakaian Keselamatan yang Lengkap di Proyek Kontruksi”, Ranah Research : Journal of Multidisciplinary Research and Development, 6(1), pp. 56-63. doi: 10.38035/rrj.v6i1.795.
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Sembiring, F., & Erfina, A. (2020). BAHASA ULAR UNTUK PEMROGRAMAN PYTHON. Sumatera Barat: Insan Cendekia.
Seong, H., Choi, H., Cho, H., & Lee, S. (2017). Vision-Based Safety Vest Detection in a Construction Scene. International Symposium on Automation and Robotics in Construction. doi:doi:10.22260/ISARC2017/0039
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Widodo, D. S. (2021). Influence of managerial performance: work motivation, leadership style and work experience (literature review study). Dinasti International Journal of Digital Business Management, 2(6), 1079–1089.
Widodo, D. S. (2022). Employee Performance Determination: Leadership Style, Individual Characteristics, And Work Culture (A Study Of Human Resource Management Literature). Dinasti International Journal of Education Management and Social Science, 3(3), 327–339.
Widodo, D. S. (2023a). Determinasi Pelatihan, Keselamatan dan Kesehatan Kerja (K3) terhadap Kepuasan Kerja. Jurnal Ilmu Multidisplin, 1(4), 956–962.
Widodo, D. S. (2023b). The Effect of Leadership Style on Turnover Intention and Job Satisfaction. International Journal of Psychology and Health Science, 1(1), 19–29.
Zhong, M., & Meng , F. (2019). A YOLOv3-based non-helmetuse detection for seafarer safety aboard merchant ships. Journal of Physics: Conference Series, 1325. doi:doi:10.1088/1742-
Amalia, P., & Aini, H. (2021). Design Validation of Revised Bloom Taxonomy Oriented Learning Devices on Elasticity Materialis For Physics Learning In Hgh School. Pillar of Physics Education, 227-234.
Bisong, E. (2019). Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners. Apress, 59-64. doi:https://doi.org/10.1007/978-1-4842-4470-8_7
Chellsya, A. A., Aulia, S., & Hadiyono, S. (2023). Implementasi Computer Vision Dalam Mendeteksi Pelanggaran Tidak Menggunakan Helm Pada Pengendara Motor. e-Proceeding of Applied Science, 9(1).
Clinton, R. M., & Sengkey, R. (2019). Purwarupa Sistem Daftar Pelanggaran Lalulintas Berbasis Mini-Komputer Raspberry Pi. Jurnal Teknik Elektro dan Komputer, 3, 182-199.
Deng, L., & Yu, D. (2004). Deep Learning: Methods and Applicationsa. Foundations and Trends® in Signal Processing, 7(3-4), 197-387. doi:http://dx.doi.org/10.1561/2000000039
Hatami, M., Tukino, Nurapriani, F., Widiyawati, & Andriani, W. (2023). DETEKSI HELMET DAN VEST KESELAMATAN SECARA REALTIME MENGGUNAKAN METODE YOLO BERBASIS WEB FLASK. Edusaintek: Jurnal Pendidikan, Sains dan Teknologi, 10(1), 21-230. doi:https://doi.org/10.47668/edusaintek.v10i1.651
Huang, G.-B., Zhu, Q.-Y., & Siew, K. C. (2006). Extreme learning machine: Theory and applications. Neurocomputing, 70(1-3), 489-501. doi:https://doi.org/10.1016/j.neucom.2005.12.126
Iskandar Maulana, D., & Rofik, M. A. (2022). Implementasi Deteksi Real Time Klasifikasi Jenis Kendaraan Di Indonesia Menggunakan Metode YOLOV5. Jurnal Pendidikan Tambusai, 6(3), 13971–13982. doi:https://doi.org/10.31004/jptam.v6i3.4825
Jupiyandi, S., Saniputra, F. R., Pratama , Y., Dharmawan, M. R., & Cholissodin, I. (2019). Pengembangan Deteksi Citra Mobil untuk Mengetahui Jumlah Tempat Parkir Menggunakan CUDA dan Modified YOLO. Jurnal Teknologi Informasi Dan Ilmu Komputer, 6(4). doi:https://doi.org/10.25126/jtiik.2019641275
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep Learning. Nature, 436–444 .
Mailoa, M. R., & Santoso, W. L. (2019). Deteksi Rompi dan Helm Keselamatan Menggunakan Metode YOLO dan CNN.
Nugroho, D. A., & Baihaqi, M. W. (2023). Improved YOLOv5 with Backbone Replacement to MobileNet V3s for School Attribute Detection. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(2). doi:https://doi.org/10.33395/sinkron.v8i3.12702
Rahman, C. R. (2020). a) Object Recognition Pengenalan objek (Object recognition) adalah teknik mengidentifikasi objek yang ada dalam gambar dan video. Ini adalah salah satu aplikasi terpenting dari pembelajaran mesin dan pembelajaran mendalam. Tujuan dari bidang ini adalah un. Biosyst, 194, 114-120. doi:doi: 10.1016/j.biosystemseng.2020.03.020
Redmon, A., Joseph, & Divalla, S. (2016). You Only Look Once: Unified, Real-Time Object Detection. ACM Int. Conf. Proceeding Ser.
Sembiring, F., & Erfina, A. (2020). BAHASA ULAR UNTUK PEMROGRAMAN PYTHON. Sumatera Barat: Insan Cendekia.
Seong, H., Choi, H., Cho, H., & Lee, S. (2017). Vision-Based Safety Vest Detection in a Construction Scene. International Symposium on Automation and Robotics in Construction. doi:doi:10.22260/ISARC2017/0039
Widodo, D. S. (2020). Manajemen Kinerja. Pdf. Cipta Media Nusantara.
Widodo, D. S. (2021). Influence of managerial performance: work motivation, leadership style and work experience (literature review study). Dinasti International Journal of Digital Business Management, 2(6), 1079–1089.
Widodo, D. S. (2022). Employee Performance Determination: Leadership Style, Individual Characteristics, And Work Culture (A Study Of Human Resource Management Literature). Dinasti International Journal of Education Management and Social Science, 3(3), 327–339.
Widodo, D. S. (2023a). Determinasi Pelatihan, Keselamatan dan Kesehatan Kerja (K3) terhadap Kepuasan Kerja. Jurnal Ilmu Multidisplin, 1(4), 956–962.
Widodo, D. S. (2023b). The Effect of Leadership Style on Turnover Intention and Job Satisfaction. International Journal of Psychology and Health Science, 1(1), 19–29.
Zhong, M., & Meng , F. (2019). A YOLOv3-based non-helmetuse detection for seafarer safety aboard merchant ships. Journal of Physics: Conference Series, 1325. doi:doi:10.1088/1742-