Author:
Celerez Jose III C.,Antipuesto Wendy E.,Aratea Daniel Reyn A.,Salvador Ivan Clint L.,Rosello Jermaine Nichole B.
Abstract
This study, which successfully addresses the shortcomings of traditional attendance-checking methods, such as human error, that are inevitable in manual attendance systems given the fact that it is time-consuming. Paper-based systems can be susceptible to forgery, as students may attempt to sign in on behalf of absent classmates. This undermines the integrity of attendance records. Introduces a fingerprint-based classroom attendance system designed using the Arduino Uno microcontroller. The research explores the feasibility of fingerprint biometrics for identity verification in educational settings. Using Arduino Uno, Fingerprint Sensor, RTC Module, and the LCD Monitor the researchers successfully developed a working prototype for the Wired Fingerprint-Based Classroom Attendance. 600 tests were applied to collect the (1.0) lowest and (2.0) highest time of the fingerprint sensor and calculate its average (1.7). The developed system operates offline, storing data securely on an SD card, making it particularly suitable for institutions in areas with restricted internet access. Comparative performance evaluations against conventional pen-and-paper methods highlight the fingerprint-based system's notable capacity, accuracy, positioning it as a transformative tool to enhance attendance tracking procedures and eliminates attendance-related issues to improve overall classroom operations.
Reference23 articles.
1. Aderonke, I. (2019). Embedded Fingerprint-Based Attendance Management System using Microcontroller. 2nd International Conference on Education and Development.
2. Aljundi, L. (2023). An intro to the Arduino IoT Cloud. Arduino.cc. https://docs.arduino.cc /learn/starting-guide/arduino-iot-cloud Asare, J. W. (2017). Biometric Attendance System. pdf. www.academia.edu.https:// www.academia.edu/330920 69/Biometric_Attendance_System_pdf
3. Cruz, J., Paglinawan, A., Bonifacio, M., Flores, A., & Hurna, E. (n.d.). Biometrics based attendance. checking using Principal Component Analysis. 2015 IEEE Region 10 Humanitarian Technology Conference (R10-HTC),2015. https://ieeexplore.ieee. org/abstract/document/7391860
4. Elijah, J., Mishra, A., Gana, M., & Musa, A. (n.d.). Staff Monitoring System Using Biometric.
5. International Journal of Engineering and Computer Science, 2015. Gabuya, A. Q., Zosa, L. T., & Minoza, J. T. (2022). The Performance of Biometric Attendance System (BAS): CTU-Tuburan Campus as case study. International Journal of Scientific and Research Publications, 12(7), 419 426. https://doi.org/10.29322/ijsrp.12.07 2022.p12748