Integration of RFID and Fingerprint Sensors in an IoT-Based Attendance System

Student attendance discipline plays an important role in ensuring the effectiveness of the learning process in schools. However, manual attendance systems commonly used in educational institutions have several limitations, including low accuracy in recording attendance time, potential data manipulation, inefficient data collection, and the absence of real-time notifications to parents. These limitations highlight the need for a more reliable and automated attendance monitoring system. This study aims to develop and evaluate an Internet of Things (IoT)-based attendance system that integrates RFID and fingerprint authentication to improve the accuracy and transparency of student attendance monitoring. The research employed an experimental approach by comparing attendance data obtained from a conventional manual system with data generated by the proposed IoT-based attendance system. The experiment involved 25 students and was conducted over four weeks, consisting of one week of manual attendance observation followed by three weeks of IoT-based attendance implementation. The developed system was also equipped with a Rule-Based Decision System (RBDS) to automatically classify student attendance status based on real-time attendance records. The results indicate that the implementation of the IoT-based attendance system improved student attendance performance. The average attendance rate increased from 72% during the manual attendance period to 74% in the first week, 82% in the second week, and 87% in the third week after the implementation of the IoT-based system. In addition, student tardiness, which was not recorded in the manual attendance system during the period of 19–23 January 2026, became measurable after the implementation of the digital system, reaching 15% during 26–30 January 2026, then decreasing to 10% during 2–6 February 2026, and further declining to 7% during 9–13 February 2026. These results demonstrate that integrating RFID, fingerprint authentication, and IoT technology can improve the accuracy, transparency, and effectiveness of student attendance monitoring.