Sistem Presensi Menggunakan Pengenalan Wajah dan Metode Deteksi Masker Pada Lingkungan Kampus

Abstract

The Covid-19 pandemic, everyone must use it when in public. This also applies on campus. Therefore, it is important to ensure that everyone in the campus environment has used masks properly and correctly. One way is to create a presence and mask detection system in the campus environment. This is done so that when students are in the campus environment or when entering the room, they can be sure to wear masks and can recognize usernames. The method used is the detection of the face when using a mask, by utilizing the face recognition library and the haar cascade method on the mask. Tested 3 times on 12 people as test data in bright conditions obtained an accuracy rate of 80%, while in light conditions it decreased to 58%-60%, then in dark or low light conditions it decreased to 17%. The conclusion that can be drawn is that the accuracy of facial recognition is quite good because it can recognize users in bright, lit, and low light conditions.