GDL

Journal from gdlhub / 2019-11-15 10:59:12
Oleh : Romi Wiryadinata, Umi Istiyah, Rian Fahrizal, Priswanto Priswanto, Siswo Wardoyo, JNTETI
Dibuat : 2017-05-10, dengan 1 file

Keyword : Sistem presensi; Deteksi wajah; Eigenface; Principal Component Analysis
Url : http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/319
Sumber pengambilan dokumen : Web

Attendance is the documentation of presence and activity in institution. A software has been made to monitor the attendance using face recognition. The software uses camera to capture the image and works on any background color. The aim of this paper is to calculate its performance with sensitivity, specificity, and accuracy using Eigenface Algorithm and Principal Component Analysis (PCA) method. Face recognition in this paper is based on Eigenface algorithm, using pixel information from images captured by webcam. The image is represented using PCA method. The software is tested using different expressions and accessories in object’s face. The performance of the software indicates 73.33%sensitivity, 52.17% specificity, and 86.67% accuracy. The successful rate in identifying the face for distance testing is 70%, while successful rate of 85% is achieved for object wearing eyeglasses and veil (jilbab). Furthermore, the successful rate for various expression is 85.33%.

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