Face Recognition Using Tiny Yolo V2 Algorithm as Attendance System - Hafidz Sanjaya; Dony Susandi; Sandi Fajar Rodiyansyah (IJISTECH (International Journal of Information System and Technology), 2020)
Nowadays many websites use the usual online attendance system which does not pay attention to safety and comfort factors so that attendance activities still have a gap of cheating. Therefore, in this study the study of the application of face recognition systems in real-time using the Tiny Yolo V2 algorithm in the online attendance system. The study was conducted with several stages starting from collecting face images, the process of image improvement (preprocessing), face detection, face recognition, and data integration using web service. The test results of 10 students, each of whom has a face image facing forward as a dataset with 4 variations of distance, each of which performs 10 different face position scenarios. Based on the test results it can be concluded that the farther the distance of the face image with the webcam, the success rate decreases, it is shown at a distance of 0.5 meters the percentage of success reaches 97% and at a distance of 2 meters 88% where 2 faces are not detected and identified at the distance is due to wearing glasses and having rather dark skin.