Prototype Fingerprint & Facial Attendance System Berbasis Raspberry Pi Dengan Metode Support Vector Machine

Abstract

Biometrics is a part of the field of technology that approaches recognition systems designed to be able to recognize and identify characteristic parts of the human body. Parts of the body in humans that are used such as faces and fingerprints are used as patterns to carry out needs in the identification process, then these body parts are used as objects for means of identifying presence. Raspberry Pi is used as a tool that processes the integrity of biometric objects that are used with the help of a webcam and fingerprint sensor to recognize someone's face and fingerprints. Then a Raspberry Pi-based Face Attendance System Prototype was designed using the Support Vector Machine method. The Support Vector Machine method based on supervised learning is used to solve classification and regression problems. By using the Support Vector Machine algorithm in MATLAB to process facial images, it is known that the accuracy value obtained by testing 25 students with facial images obtained 375 images divided from one student consisting of 15 images. 250 images of training data were tested with a result of 65.20% and 125 images of test data with a result of 66.40%.