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Timekeeping and Immediate Monitoring of Employees by Consistently Advocating Time Consciousness and Honesty Using Enhanced Attendance Monitoring System (TIME CATCH Using EAMS)

Ronald Bautista Rivera, Maricar Bulan Asis and Oscar Gacutan Bangayan

Pertanika Journal of Tropical Agricultural Science, Volume 31, Issue 1, January 2023

DOI: https://doi.org/10.47836/pjst.31.1.18

Keywords: Attendance, QR code, face recognition

Published on: 3 January 2023

Attendance management methods that use QR codes and face recognition technology to identify and verify an individual’s features are widely used in many aspects of people’s lives nowadays, notably in pandemic situations where contact-less systems are used. In this paper, the development of enhanced attendance monitoring system using was introduced. The Isabela State University Angadanan Campus has implemented a biometric attendance monitoring system. However, it is limited to the number of employees’ registrations, leave management and generation of Daily Time Record. The biometric system can only store 60 employees in every device, leave application and credits cannot be catered by the system and the Daily Time Record is not auto-generated and auto-formatted. For this reason, an enhanced attendance monitoring system was developed. The system uses a camera and QR Code reader to take attendance electronically, and the attendance records be saved in a database. It can store multiple number of employees, process leave application, manage remaining leave credits, and provide auto-generated Daily Time Record. This method, on the other hand, reduces the requirement for fixed materials and employees to retain records. From the developed system and the gathered data, it has addressed the problem of the conventional way of checking employee’s attendance. The general mean of 4.72 shows that the software quality of the system based on ISO 25010 is found to be functional that the users have strongly agreed on the different characteristics of the system as it addresses the issues in the current attendance monitoring system of ISU.

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ISSN 1511-3701

e-ISSN 2231-8542

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