Perancangan Teknologi Radio Frequency Identification Dalam Sistem Presensi Peserta Didik Berbasis Internet of Things di Sekolah Menegah Pertama Sejahtera 2 Cileungsi

Authors

  • Maulana Yusuf Widsono Universitas Muhammadiyah Prof. Dr. HAMKA, Indonesia
  • Nuroji Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta, Indonesia, Indonesia

DOI:

https://doi.org/10.29240/arcitech.v5i1.13968

Keywords:

Attendance, IoT, Telegram, RFID, Esp32

Abstract

The manual student attendance system at SMP Sejahtera 2 Cileungsi presents several inefficiencies, such as susceptibility to recording errors, time-consuming procedures, and difficulties in accurately summarizing attendance data. Previous studies have proposed RFID and IoT-based systems to improve efficiency, yet most lack features for real-time parental notification. This study aims to develop an automated student attendance system using Radio Frequency Identification (RFID) integrated with the Internet of Things (IoT) and a Telegram bot for immediate communication with parents. The system was developed using the prototyping method, allowing for iterative refinement based on user needs. Attendance is recorded through RFID cards tapped on a reader device, with data stored in a database and exportable to PDF and Excel formats. Black box testing was conducted to validate system functionality. The results indicate that the system enhances accuracy, efficiency, and parental involvement by providing real-time updates. This research contributes to smart education technology by offering a scalable and interactive attendance model that supports administrative digital transformation in schools.

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Author Biography

Nuroji, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta, Indonesia

Program Studi Teknik Informatika

References

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Published

30-06-2025

How to Cite

Yusuf Widsono, M., & Nuroji. (2025). Perancangan Teknologi Radio Frequency Identification Dalam Sistem Presensi Peserta Didik Berbasis Internet of Things di Sekolah Menegah Pertama Sejahtera 2 Cileungsi. Arcitech: Journal of Computer Science and Artificial Intelligence, 5(1), 125–147. https://doi.org/10.29240/arcitech.v5i1.13968

Issue

Vol. 5 No. 1 (2025): June 2025

Section

Articles

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