Optimalisasi Metode Deteksi Wajah berbasis Pengolahan Citra untuk Aplikasi Identifikasi Wajah pada Presensi Digital

Abstract

Graphical abstract Abstract In the era 2000s, image-based technology evolved so rapidly along with technological advances. One application in the field of face detection research. Research on face detection was first introduced by Viola and Jones researchers in 2001. In addition, this research is motivated by the presence of student attendance on campus which is still manual and not a few students who cheated when present. The topic of this research is optimization of face detection based on image processing so as to get the right technique / method in detecting face image and it can reduce false positive error for non-face object in the classroom. This research was conducted in campus IST Akprind Yogyakarta with the aim of applying automatic presences for student attendance. The methods proposed in this study include the Viola-Jones method for facial detection, feature extraction using 12 color statistics features, and classification process using the Multi Layer Perceptron classifier to optimize the detection process. By using 309 data of face candidates, this research was able to detect face object with accuracy value of 82%, specificity value of 35%, and sensitivity value of 97%. This is shows that the addition of 12 color statistic feature extraction and Multi Layer Perceptron can increase the accuracy value of 6% and the spesificity value of 11%.