Sistem Pengenalan Wajah Real-Time Menggunakan YOLOv7 untuk Akses Gedung TVRI Palembang Berbasis Web

The development of information and communication technology today has had a significant impact on various aspects of life, including in the field of security. The use of face recognition is one of the facial recognition techniques, where the results of the camera capture will be matched with photos or facial curve textures that already exist in the database. The system is widely applied using various methods and artificial intelligence, one of which is YOLO (You Only Look Once). The purpose of this study is to design, develop, and identify challenges in implementing a real-time facial recognition system using web-based YOLOv7 that can detect the faces of people entering the TVRI Palembang building, then photos and times when a person's face is not detected will be stored in the database. The data used comes from literature studies, data collection obtained from photos of TVRI television station employees' faces, software design with technology selection, user interface design, and algorithm structures that will be used. After going through these stages, a system implementation was carried out for the application of the system and analysis of the data results obtained. The results showed that the face detection system using YOLOv7 showed very good performance. In 100 training epochs, the system achieved 96,6% face detection accuracy and 90% face recognition accuracy, successfully identifying almost all registered faces and detecting faces in real time. This system produces high accuracy in detecting faces and almost all faces that should be recognized are successfully detected.