IMPLEMENTASI FACE RECOGNITION SEBAGAI SISTEM PRESENSI MENGGUNAKAN METODE RESIDUAL NEURAL NETWORK (Studi Kasus: SMK Bina Teknologi Purwokerto)

Attendance is a list of attendance of employees, students, and so on which contains the time of arrival or departure and the reason for the statement of attendance. Several attendance systems have so far been carried out manually, using excel, website systems and using fingerprints. The emergence of Covid-19 cases resulted in everyone being obliged to comply with the rules of health protocols. The employee attendance recording system that runs at SMK Bina Teknologi Purwokerto uses a fingerprint. Fingerprint is a tool that takes information from fingerprint biometrics. In the Covid-19 pandemic, attendance recording using fingerprints is possible for someone to contract the Covid-19 virus because it involves employees in direct contact with fingerprint sensors that are used en masse. To solve this problem, a study was conducted that aims to implement the presence of employees and teachers of SMK Bina Teknologi Purwokerto with face detection during the Covid-19 pandemic using the Residual Neural Network face detection algorithm. This study uses facial data of employees and teachers at SMK Bina Teknologi Purwokerto. From model testing, the accuracy value of the training data results is 100% and questionnaire testing for user satisfaction reaches 86.09%.