Utilising QR-Code of Covid-19 Vaccine for Attendance Using Extreme Programming Method

PEMANFAATAN QR-CODE VAKSIN COVID-19 UNTUK ABSENSI MENGGUNAKAN METODE EXTREME PROGRAMMING

  • Ermin Ermin Universitas Muhammadiyah Sorong
  • Rendra Soekarta Universitas Muhammadiyah Sorong
  • Muhammad Insan Abdillah Universitas Muhammadiyah Sorong
https://doi.org/10.35457/antivirus.v17i2.3217
Abstract views: 168 , PDF downloads: 180
Keywords: Attendance, Student, COVID-19 Vaccine, QR Code, Extreme Programming

Abstract

The digital attendance system enables more efficient data processing, real-time time monitoring, and reduces human errors in the recording process. One of the schools that has developed this technology is SMK Negeri 4 Kota Sorong. This is related to the last two years, where almost everyone has been required to receive the COVID-19 vaccine for prevention and monitoring of student attendance at school. To support the monitoring of student attendance at school, a web-based COVID-19 Vaccine QR-Code utilization system is needed at SMK Negeri 4 Sorong, Southwest Papua. This student attendance system has three access levels, which are divided into admin, teachers, and parents. This research uses PHP programming language and MySQL database. The development of this system is carried out using the Extreme Programming method, which includes steps such as problem identification, data collection, applying the Extreme Programming method, and implementation. The school attendance system, which has been built with its features, has been proven to work perfectly through feature testing using black-box testing with a 100% success rate. From the results of this testing, the utilization of the COVID-19 Vaccine QR-Code can be used for attendance and departure monitoring.

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References

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Published
2023-11-30
How to Cite
[1]
E. Ermin, R. Soekarta, and M. I. Abdillah, “Utilising QR-Code of Covid-19 Vaccine for Attendance Using Extreme Programming Method: PEMANFAATAN QR-CODE VAKSIN COVID-19 UNTUK ABSENSI MENGGUNAKAN METODE EXTREME PROGRAMMING”, antivirus, vol. 17, no. 2, pp. 193-202, Nov. 2023.
Issue
Vol. 17 No. 2 (2023): November 2023
Section
Articles

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