Face-Nest,带有时间戳日志的面部识别考勤系统:一种信息系统安全方法

Q2 Social Sciences
Luthfi Jaka Satria, I. F. Kamsin, N. Zainal
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引用次数: 0

摘要

在技术进步和发展的不断扩大的世界中,许多新的概念和技术正在向世界展示,旨在简化当前的流程或创新解决现有问题的方法。疫情带来了新的运营条件,迫使包括教育部门在内的许多部门实现全面数字化。因此,本研究旨在开发人脸识别考勤系统,以促进方便和准确的考勤。这对于确保记录学生出勤的时间可以在不牺牲准确性的情况下最小化是至关重要的,并且从理论上限制了教育环境中代理出勤的发生。定量研究在马来西亚进行,涉及82名来自私立大学的学生。这对于确保学生能够参与教学过程,同时创造一个有意义的学习环境至关重要。使用社会科学统计软件包(SPSS)软件对数据进行分析。研究结果表明,人脸识别考勤系统通过限制学生之间的代理出勤,有助于提高在线环境下的教育质量。因此,本研究结果有助于为利用人脸识别考勤系统提高教育机构的出勤率提供研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face-Nest, Facial Recognition Attendance System with Timestamp Logs: An Information System Security Approach
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.
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来源期刊
CiteScore
2.80
自引率
0.00%
发文量
120
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