Face-Nest, Facial Recognition Attendance System with Timestamp Logs: An Information System Security Approach

Abstract

In the ever-expanding world of technological advancement and development, many new concepts and technologies are being presented to the world that aim to streamline current processes or innovate an approach to an existing problem. The pandemic has brought forward new operating conditions that have forced many to make the leap to go fully digital, including the education sector. Therefore, this conducted study aims to develop facial recognition attendance system that promotes convenience and accurate attendance marking. This is crucial to ensure time taken to record students’ attendance could be minimize without any sacrifice in accuracy, and theoretically limit the occurrence of proxy attendance within the education setting. Quantitative research was conducted in Malaysia, which involved 82 students from private university. This is crucial to ensure students are able to engage in the teaching and learning process, and at the same time develop a meaningful learning environment. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) software. Research findings show that the facial recognition attendance system contribute to improve the quality of education within online settings by limiting the occurrence of attendance proxying among students. Therefore, this finding contributes by providing a research direction for improving attendance in education setting by utilizing facial recognition attendance system.