Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications
Wikaria Gazali
Mathematics and Statistics Department, School of Computer Science, Bina Nusantara University Jl. KH. Syahdan No. 9, Jakarta 11480, Indonesia
Computer Science & IT Engineering Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : ComTech: Computer, Mathematics and Engineering Applications

 1 
Sistem Kontrol Akses Berbasis Real Time Face Recognition dan Gender Information Nurmala, Putri; Gazali, Wikaria; Budiharto, Widodo
ComTech: Computer, Mathematics and Engineering Applications Vol 6, No 2 (2015): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v6i2.2264

Abstract

Face recognition and gender information is a computer application for automatically identifying or verifying a person's face from a camera to capture a person's face. It is usually used in access control systemsand it can be compared to other biometrics such as finger print identification system or iris. Many of face recognition algorithms have been developed in recent years. Face recognition system and gender information inthis system based on the Principal Component Analysis method (PCA). Computational method has a simple and fast compared with the use of the method requires a lot of learning, such as artificial neural network. In thisaccess control system, relay used and Arduino controller. In this essay focuses on face recognition and gender - based information in real time using the method of Principal Component Analysis ( PCA ). The result achievedfrom the application design is the identification of a person’s face with gender using PCA. The results achieved by the application is face recognition system using PCA can obtain good results the 85 % success rate in face recognition with face images that have been tested by a few people and a fairly high degree of accuracy.
Co-Authors Alexander A S Gunawan, Alexander A S Heni Kurniaty, Heni Nurmala, Putri Widodo Budiharto