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ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
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, EBSCO,
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Acceptance Rate:
17%
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Impact Factor 2023: 0.9
4.2
2023
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Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2025-04-02
Included in Chinese Academy of Sciences (CAS) Journal Ranking 2025: Q4 in Computer Science
2025-03-20
JAIT Vol. 16, No. 3 has been published online!
2025-02-27
JAIT has launched a new Topic: "Human-Computer Interaction (HCI) in Modern Technological Systems."
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2021
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Volume 12, No. 3, August 2021
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Application of “Face Recognition” Technology for Attendance Management System
Chandra
1
, M. Feisal Fransditya Mulyananda
1
, Michael Andrew Gunawan
1
, Ford Lumban Gaol
2
, and Tanty Oktavia
3
1. Mobile Application & Technology Program, Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia
2. Computer Science Department, BINUS Graduate Program-Doctor of Computer Science, Bina Nusantara University, Jakarta, Indonesia
3. Information System Department, School of Information Systems, Bina Nusantara University, Jakarta, Indonesia
Abstract
—The attendance management system is a system that needed for learning activity in a University. In some University, the attendance management system has been used tapping system which using NFC technology. Actually, that attendance management system is effective for managing each of attendance information. However, until now we can still see many cheats for this attendance system. For example, leave their cards to their classmates and tell them to tap for them. For that, one of the many effective solutions to resolve that problem is to add face recognition technology in the current attendance system. In our experiment, we know that to add face recognition to the current attendance management system surely need a camera and also face dataset for the system. At the beginning, we need at least 9 images with different emotions and face positions to let the system recognizes one’s face. To make this system more accurate at recognizing one's face, we would update the face dataset in every face recognizing process.
Index Terms
—attendance management system, face recognition, NFC, camera, Infrared, face, face dataset
Cite: Chandra, M. Feisal Fransditya Mulyananda, Michael Andrew Gunawan, Ford Lumban Gaol, and Tanty Oktavia, "Application of “Face Recognition” Technology for Attendance Management System," Journal of Advances in Information Technology, Vol. 12, No. 3, pp. 260-266, August 2021. doi: 10.12720/jait.12.3.260-266
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
13-SC402_Indonesia
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