Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Angga Wahyudi Kurniawan Pratama
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Pengenalan Citra Wajah menggunakan Ekstraksi Fitur Ruang Warna YCbCr dan Metode Principle Component Analysis (PCA) untuk Presensi Mahasiswa Otomatis Angga Wahyudi Kurniawan Pratama; Muh. Arif Rahman; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Face is a part of the human body that is very influential in everyday life. Most humans recognize a person by face. From the uniqueness of the face, there are innovations about automatic presence using faces that are more efficient than manual presence which is prone to manipulation. However, in reality, automatic presence based on facial recognition has a disadvantage of high light intensity, which makes facial images look biased. This problem can be overcome by approaching the YCbCr color space which is able to overcome the high light intensity in the image. The essence of automatic presence is the process of detecting and recognizing human facial images. In this study, only focus on facial recognition with the YCbCr color space feature extraction method and the Principle Component Analysis method. The results from the PCA value will be calculated using the Eucledian Distance to determine the closeness between the training image and the test image. In this test using two scenarios, the first test scenario uses a test image without light that is able to get an accuracy of 84%. The second test scenario uses a test image with a light beam capable of obtaining an accuracy of 52%.
Co-Authors Bayu Rahayudi Muh. Arif Rahman