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Randomized QR-code scanning for a low-cost secured attendance system

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 4 (2022)

DOI
10.11591/ijece.v12i4.pp3762-3769
ISSN
2722-2578, 2088-8708
Published
2022-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Human resource management requires good documentation and good data processing. In workspaces such as offices and factories, employee salaries are determined by calculating attendance at each hour of work. Tracking and collecting attendance data for a large number of employees is a difficult thing to do. We need a secure system to facilitate the process of collecting and tracking presence data. We propose an attendance system that uses random quick response code (QR-codes) as one time password (OTP) to improve security. Employees are required to scan the QR-code within ten seconds before it is changed and randomized each time. The proposed attendance system facilitates data collection using employees’ smartphones and Mac-Address as unique identification numbers. The system is able to track employees’ arrival and departure times. We have implemented the system at the local university to collect lecturer attendance data then analyze its security and statistic in all scanning activities. The average time needed by a user to authenticate their presence in the system is 25.8877 seconds. The steps needed to sign in and out from the system are fewer than other previous researches. Those findings tell us that the approach is straightforward and more uncomplicated than other proposed methods. We conclude that randomized QR-code scanning is a relevant scheme to be applied in a secure attendance system.

Collaboration network of the authors

6 authors · 11 co-authorship links · 1 across different organisations

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  • Universitas Muhammadiyah Bengkulu
  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
GunawanUniversitas Halu Oleo1
Ardi WijayaAffiliation unknown1
Andi YahyaAffiliation unknown1
RG Guntur AlamAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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