Deteksi Penggunaan Masker dan Klasifikasi Secara Real Time Melalui Video Webcam Dengan Metode YOLO
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Abstract
The use of masks is currently important to prevent the spread of the virus. However, there are often people who do not wear masks in public places. Therefore, a real-time mask detection system is needed via webcam video. This system uses the You Only Look Once (YOLO) method to detect faces and classify whether the person is wearing a mask or not. The YOLO model is used to detect and classify masks in images and is trained using datasets from kaggle. The results for YOLO show the detection accuracy for masks is 92% using training data.
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This work is licensed under a Jurnal Komunikasi Creative Commons Attribution-ShareAlike 4.0 International License.
References
Megawan, Sunario dan Lestari, Wulan Sri, “Deteksi Spoofing Wajah Menggunakan Faster R-CNN dengan Arsitektur Resnet50 pada Video”, Jurnal Nasional Teknik Elektro dan Teknologi Informasi, Vol. 9, Nomor 3, (Agustus, 2020) h. 261-267, 2 September 2022
Hartono, Ivan; Noertjahyana, Agustinus; dan Santoso, Leo Willyanto, Deteksi Masker Wajah dengan Metode Convolutional Neural Network, https://publication.petra.ac.id/index.php/teknik-informatika/article/download/12042/10576, 2 September 2022
Budiman, Bunardi; Lubis, Chairisni; dan Perdana, Novario Jaya, “Face Mask Detection Using the Convolutional Neural Network”, Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) Vol. 9 No. 1 (Januari, 2021), 2 September 2022