Facial Recognition Technology on Attendance Tracking

  • Shalin Binti Shaheezam Khan Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
  • Hamimah Ujir Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
  • Muhammad Quazy Bin Razali Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
  • Sarfiza Binti Othman@Osman Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
DOI: https://doi.org/10.33736/jcsi.5541.2023
Keywords: Attendance Tracking, Facial Recognition Technology, Acceptance Status, Threats, User Behavior

Abstract

Numerous airports have opted to replace traditional check-in systems with advanced Attendance Tracking technology that incorporates face recognition. This paper presents the findings of a research study conducted among individuals aged 20 to 60, currently employed in either government or private sectors. The results shed light on the respondents' attitudes towards and acceptance of this advanced technology, as well as its effectiveness. Technology Acceptance Model (TAM) is implied together with Perceived System Quality (PSQ) in this study. Perceived ease of use (PEOU), perceived usefulness (PU), attitude (ATT), behavioral intention to use (BI), and actual system use are also included in measuring the effect. The outcomes of this investigation indicate a wide acceptance of this technology, particularly in the context of attendance tracking systems. The respondents demonstrate a favorable attitude towards the integration of face recognition technology in various aspects of their lives. The survey encompasses several key components, namely demographic information, awareness of facial recognition technology, and perceptions of system quality. These results provide insights into the viability and acceptance of face recognition technology, validating its potential implementation in attendance tracking systems.

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Published
2023-08-29
How to Cite
Binti Shaheezam Khan, S., Ujir, H., Bin Razali, M. Q., & Binti Othman@Osman, S. (2023). Facial Recognition Technology on Attendance Tracking. Journal of Computing and Social Informatics, 2(2), 9-26. https://doi.org/10.33736/jcsi.5541.2023
Issue
Vol 2 No 2 (2023): Journal of Computing and Social Informatics
Section
Articles

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