Open AccessAbsensi Pengenalan Wajah Menggunakan Menggunakan Algoritma Eigenface Berbasis Web
Author(s) -
Satria Putra Putra,
Iskandar Fitri,
Sari Ningsih
Publication year - 2021
Publication title -
journal of applied informatics and computing
Language(s) - English
Resource type - Journals
ISSN - 2548-6861
DOI - 10.30871/jaic.v5i1.2711
Subject(s) - attendance , computer science , government (linguistics) , covid-19 , process (computing) , key (lock) , pandemic , facial recognition system , artificial intelligence , computer security , pattern recognition (psychology) , medicine , political science , infectious disease (medical specialty) , law , operating system , philosophy , linguistics , disease , pathology
During the Covid-19 virus pandemic as it is currently being experienced in Indonesia is very rapidly spreading, forcing the government to impose a PSBB (Pembatasan Sosial Bersekala Besar) system in several regions in Indonesia. With the government regulation on health protocols, many companies must take action to minimize the spread of the Covid-19 virus. In this situation with daily activities opens opportunities for the Covid-19 virus to spread very quickly, especially in the office sphere. The spread of the Covid-19 virus could be through an attendance system that still uses finger print tools used to collect employee attendance data. In this study, attendance application developed using facial recognition method as key for employee data retrieval. This method of facial recognition is applied in real time with a certain distance and lighting. Eigenface algorithm is used as a training process for employees' faces that have been inputted before. The results of the training data will be saved to a database which is then used as a key to recognize the faces of employees who will perform attendance. In the results of the trial the attendance data application will enter when the level of facial recognition is above 70%.