Desmira, Mustofa Abi Hamid, Muhammad Nurtanto
This study aims to develop and analyze facial recognition patterns, a biometric-based approach to identify individuals through facial features. Such biometric patterns can be used as a tool to verify the presence of a student. Face recognition technology utilizing Raspberry Pi to assess the appropriateness of biometric patterns. The facial matching process is employed to ascertain student attendance in class. The Principal Component Analysis (PCA) technique is employed in the face detection procedure. The sample testing was carried out on a group of fifty students, with each student supplying thirty different facial photos. 1,500 images were processed utilizing the PCA algorithm within the OpenCV library. A 95% accuracy rate was achieved with the photos that were obtained, which have a resolution of 640x480 pixels. © 2025 World Scientific and Engineering Academy and Society. All rights reserved.
Department of Electrical Engineering Vocational Education, Universitas Sultan Ageng Tirtayasa, Ciwaru Raya Street No. 25, Cipare, Serang, Banten, Serang City, 42117, Indonesia; Graduate School of Technological and Vocational Education, Universitas Negeri Yogyakarta, Colombo Street, Karang Malang, Caturtunggal, Depok, Sleman Regency, Yogyakarta, 55281, Indonesia; Department of Technological and Vocational Education, Universitas Negeri Jakarta, Rawamangun Muka Street, Rawamangun, Special Capital Region of Jakarta, East Jakarta, 13220, Indonesia; Center for Vocational and Technical Education and Training (Voctech), Mangga Street, BIP Blok H10 No.7, Unyur, Serang, Banten, Serang City, 42111, Indonesia
