Implementasi Sistem Keamanan Brankas Berbasis Face Recognition Menggunakan Algoritma YOLO dengan Verifikasi Fingerprint

Current technological developments make security crucial in protecting important documents. Safes are commonly used for storage but remain vulnerable to burglary despite conventional locks. Based on data from the Central Bureau of Statistics (BPS) in 2023, aggravated theft was the most frequent crime with 62,872 reported cases. This highlights the need to improve safe security by adding biometric techniques such as face recognition and fingerprint verification. This study proposes a layered security system combining face recognition using the YOLO algorithm and fingerprint sensors. The system uses an ESP32-CAM to capture facial images and an ESP32 microcontroller to control a solenoid lock, fingerprint sensor and buzzer alarm. Face recognition testing on two users showed, the trained YOLO model achieved an accuracy of 83.33%, precision of 83,33% and recall of 100%. from 12 trials, with two failures due to poor lighting conditions. Fingerprint testing on 10 samples, five fingers from each of two users, showed successful recognition of all fingerprints with an average response time of 1.41 seconds. The integration of face and fingerprint biometrics significantly enhances safe security and minimizes unauthorized access risks.