Prototype Face Attendance System Berbasis Raspberry PI Menggunakan Metode Eigenface di Program Studi Pendidikan Vokasional Teknik Elektro Untirta

Fikri Firmansyah (Universitas Sultan Ageng Tirtayasa)
Desmira Desmira (Universitas Sultan Ageng Tirtayasa)
Endi Permata (Universitas Sultan Ageng Tirtayasa)
Didik Aribowo (Universitas Sultan Ageng Tirtayasa)

RESLAJ: RELIGION EDUCATION SOCIAL LAA ROIBA JOURNAL
Vol 5 No 5 (2023): Reslaj: Religion Education Social Laa Roiba Journal

Face recognition is one of the pattern recognition approaches for the purposes of identifying a person's face with a biometric approach. From this biometric pattern, it can be used as a means to identify the presence of a student. Assisted by the Raspberry Pi, this facial recognition can be done and it can be concluded whether the biometric pattern matches or not. This suitability will be a reference to indicate the presence of a student. So a Raspberry Pi-based Prototype Face Attendance System was made using the Eigenface method. Eigenface is an algorithm that works based on Principle Component Analysis (PCA). Tests were carried out by testing 30 students with a total of 30 photo samples per individual resulting in an accuracy value of 78.85% and error value is 21.15%.