Menghitung Akurasi Sistem Deteksi Masker Berdasarkan Arah Pandangan Kepala Objek

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Furqan Rasyid
Muhammad Syukri Mustafa
Andi Asvin Mahersatillah Suvardi


During this Covid-19 pandemic, the use of masks is highly recommended. The use of masks is very good to stop the spread of the virus. This is why many studies have created systems to assist humans in detecting the use of masks. However, from several existing studies, no research has been found that measures the accuracy of the detection system based on the direction of the object's head view, especially those using the fourth version of yolo (yoloV4). This study calculates accuracy based on 5 viewing angles, namely: (0, 45, 90) degrees sideways, up, and down. The distance between the camera and the test object is 1 meter. The results of the calculation, obtained very satisfactory results, namely 100% for each point of view. While the time required for the system to detect the fastest when the head position is straight ahead (0 degrees) with a time of 3.09 seconds. The longest time occurred when the head down position was 3.89 seconds

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How to Cite
Rasyid, F., Mar’atuttahirah, Mustafa, M. S., & Suvardi, A. A. M. (2022). Menghitung Akurasi Sistem Deteksi Masker Berdasarkan Arah Pandangan Kepala Objek. Computer Science Research and Its Development Journal, 14(3), 203–214.


I. Ahmed, M. Ahmad, J. J. P. C. Rodrigues, G. Jeon, and S. Din, “A deep learning-based social distance monitoring framework for COVID-19,” Sustain Cities Soc, vol. 65, p. 102571, Feb. 2021, doi: 10.1016/j.scs.2020.102571.

M. F. Rasyid, D. Imran, and A. A. Mahersatillah, “Prediksi penyebaran Sub Varian omicron di Indonesia menggunakan Machine Learning,” SISITI : Seminar Ilmiah Sistem Informasi dan Teknologi Informasi, vol. 11, no. 1, Art. no. 1, Aug. 2022, Accessed: Sep. 30, 2022. [Online]. Available:

A. HendroTriatmoko, “Penggunaan Metode Viola-Jones dan Algoritma Eigen Eyes dalam Sistem Kehadiran Pegawai,” vol. 8, no. 1, p. 6, 2014.

S. Singh, U. Ahuja, M. Kumar, K. Kumar, and M. Sachdeva, “Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment,” Multimed Tools Appl, vol. 80, no. 13, pp. 19753–19768, May 2021, doi: 10.1007/s11042-021-10711-8.

“YOLO V4 | Social Distancing and Face Mask Detection using YOLO V4,” Analytics Vidhya, May 03, 2021. (accessed Feb. 01, 2022).

K. Bhambani, T. Jain, and K. A. Sultanpure, “Real-time Face Mask and Social Distancing Violation Detection System using YOLO,” in 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), Oct. 2020, pp. 1–6. doi: 10.1109/B-HTC50970.2020.9297902.

S. L. Edmonds-Wilson, N. I. Nurinova, C. A. Zapka, N. Fierer, and M. Wilson, “Review of human hand microbiome research,” J Dermatol Sci, vol. 80, no. 1, pp. 3–12, Oct. 2015, doi: 10.1016/j.jdermsci.2015.07.006.

S. G. Schauer, J. F. Naylor, M. D. April, B. M. Carius, and I. L. Hudson, “Analysis of the Effects of COVID-19 Mask Mandates on Hospital Resource Consumption and Mortality at the County Level,” South Med J, vol. 114, no. 9, pp. 597–602, Sep. 2021, doi: 10.14423/SMJ.0000000000001294.

A. Sopian, “Sistem Deteksi Kematangan Tandan Buah Segar Kelapa Sawit dengan Metode YOLOv4,” Thesis, IPB University, 2021. Accessed: Feb. 13, 2022. [Online]. Available:

A. I. B. Parico and T. Ahamed, “Real Time Pear Fruit Detection and Counting Using YOLOv4 Models and Deep SORT,” Sensors (Basel), vol. 21, no. 14, p. 4803, Jul. 2021, doi: 10.3390/s21144803.

J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You Only Look Once: Unified, Real-Time Object Detection,” Jun. 2016, pp. 779–788. doi: 10.1109/CVPR.2016.91.

A. Bochkovskiy, C.-Y. Wang, and H.-Y. M. Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv:2004.10934 [cs, eess], Apr. 2020, Accessed: Feb. 16, 2022. [Online]. Available:

“YOLOv4 Darknet Object Detection Model,” Roboflow. (accessed Feb. 13, 2022).

M. Rasyid, Z. Zainuddin, and A. Andani, “Early Detection of Health Kindergarten Student at School Using Image Processing Technology,” Jun. 2019. Accessed: Dec. 21, 2021. [Online]. Available:

V. T. Mohit, R. V. Kumar, and B. A. M.e, “face mask detection and recognition using opencv tensor flow and machine learning,” International Journal of Advanced Research in Computer Science Engineering and Information Technology, vol. 6, no. 3, pp. 1608–1613, Apr. 2021, Accessed: Dec. 24, 2021. [Online]. Available:

M. Tian and Z. Liao, “Research on Flower Image Classification Method Based on YOLOv5,” J. Phys.: Conf. Ser., vol. 2024, no. 1, p. 012022, Sep. 2021, doi: 10.1088/1742-6596/2024/1/012022.