Development of Employee Attendance Management Information System During the Covid-19 Pandemic Based on Website using QR Code and PHP Native

Ahmad Habib, Moch Dzawil Haiat, Balok Hariadi

Abstract


Hero Web Design is a small-scale company that is growing, the company is engaged in technology. Attendance activities at Hero Web Design still use the conventional method, every day employees carry out attendance activities manually. This results in fraud, loss, and damage to the processed data because they are not integrated. As a result, with the emergence of these problems the company could not develop. With the problems that Hero Web Design has, here an online attendance information system is made with a QR-Code and face detection using the Scrum method. In this study using the Scrum method using 3 Sprints, each Sprint has a process of not more than one month. The data sources used in this study are observational data in the form of attendance management activities and report management. The second data source is interview data in the form of an answer from a question-and-answer discussion with Hero Web Design. The third data source is literature study data in the form of supporting journals that have similar research. A website-based attendance management information system with a program working process using the PHP programming language, javascript, CSS, and bootstrap framework. The results of the information system that has been created will be tested using the black box method. This method aims to check for missing or incorrect functions, interfaces, performance, program initialization and output errors, data structures, or database access errors. Furthermore, from making this system, it is hoped that it can be used as a remote or online attendance without having to come face to face and overcome the problems found in Hero Web Design.


Keywords


Attendance; Quick Response Code; Employee; Information System

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DOI: https://doi.org/10.24167/sisforma.v9i2.4384

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SISFORMA: Journal of Information Systems | p-ISSN: 2355-8253 | e-ISSN: 2442-7888 | View My Stats

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