Applying Biometric Technology in School Attendance and Security Management
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In today's digital era, security and efficiency in attendance management in the school environment are very important. Biometric technology has become a new trend in improving security and optimizing the attendance recording process, replacing manual systems prone to errors and fraud. This research aims to analyze the effectiveness of applying biometric technology in school attendance and security management. Specifically, this research focuses on evaluating how this technology can reduce cheating, increase the accuracy of attendance data, and strengthen school security systems. This research uses quantitative methods with a case study approach at five schools implementing a biometric system. Data was collected through surveys of school administrators and direct observation of the registration and identity verification processes at these schools. Data analysis was carried out using descriptive and inferential statistics. This research shows that using biometric technology significantly increases the efficiency and accuracy of the attendance recording system. Student attendance is recorded quickly and accurately, with virtually no cheating. This technology also strengthens the security system by ensuring that only verified individuals can access school facilities. This research concludes that applying biometric technology in school attendance and security management has proven very effective. This technology optimizes attendance and improves security, providing a safe environment for students and staff. The research recommends wider adoption of biometric technology in other schools to improve security and operational efficiency.
A Study on the Protection of Biometric Information against Facial Recognition Technology. (2023). KSII Transactions on Internet and Information Systems, 17(8). https://doi.org/10.3837/tiis.2023.08.009
Abomhara, M., Yayilgan, S. Y., Nweke, L. O., & Székely, Z. (2021). A comparison of primary stakeholders’ views on the deployment of biometric technologies in border management: Case study of SMart mobILity at the European land borders. Technology in Society, 64, 101484. https://doi.org/10.1016/j.techsoc.2020.101484
Aldana-Aguirre, J. C., Pinto, M., Featherstone, R. M., & Kumar, M. (2017). Less invasive surfactant administration versus intubation for surfactant delivery in preterm infants with respiratory distress syndrome: A systematic review and meta-analysis. Archives of Disease in Childhood - Fetal and Neonatal Edition, 102(1), F17–F23. https://doi.org/10.1136/archdischild-2015-310299
Ali, N. S., Alhilali, A. H., Rjeib, H. D., Alsharqi, H., & Sadawi, B. A. (2022). Automated attendance management systems: Systematic literature review. International Journal of Technology Enhanced Learning, 14(1), 37. https://doi.org/10.1504/IJTEL.2022.120559
Alrahawe, E. A. M., Humbe, V. T., & Shinde, G. N. (2021). A Biometric Technology?Based Framework for Tackling and Preventing Crimes. In S. K. Pani, S. K. Singh, L. Garg, R. B. Pachori, & X. Zhang (Eds.), Intelligent Data Analytics for Terror Threat Prediction (1st ed., pp. 133–160). Wiley. https://doi.org/10.1002/9781119711629.ch7
Bartfeld, J. S., Berger, L., Men, F., & Chen, Y. (2019). Access to the School Breakfast Program Is Associated with Higher Attendance and Test Scores among Elementary School Students. The Journal of Nutrition, 149(2), 336–343. https://doi.org/10.1093/jn/nxy267
Calvo-Sanz, J., Poyales, F., Zhou, Y., Arias-Puente, A., & Garzón, N. (2022). Agreement between the biometric measurements used to calculate the size of the implantable collamer lenses measured with four different technologies. Indian Journal of Ophthalmology, 70(5), 1586. https://doi.org/10.4103/ijo.IJO_2217_21
Clarke, F. C., & Burt, W. L. (2019). A Study of the Effects of Charter Schools on Student Achievement, Attendance, and Selected Mitigating Factors in a Midwestern State’s Midsize Urban School Districts. Education and Urban Society, 51(9), 1265–1290. https://doi.org/10.1177/0013124518785015
Corcoran, S., & Kelly, C. (2023). A META?ETHNOGRAPHIC understanding of children and young people’s experiences of extended school NON?ATTENDANCE. Journal of Research in Special Educational Needs, 23(1), 24–37. https://doi.org/10.1111/1471-3802.12577
Fernando, D. H., Kuhaneswaran, B., & Kumara, B. T. G. S. (2022). A Systematic Literature Review on the Application of Blockchain Technology in Biometric Analysis Focusing on DNA: In B. J. Holland (Ed.), Advances in Library and Information Science (pp. 77–99). IGI Global. https://doi.org/10.4018/978-1-6684-4755-0.ch005
Fu, R., Wang, L., Huo, X., Pei, P., Jiang, H., & Fu, Z. (2022). An Improved Biometric Fuzzy Signature with Timestamp of Blockchain Technology for Electrical Equipment Maintenance. Energy Engineering, 119(6), 2621–2636. https://doi.org/10.32604/ee.2022.020873
Hamidi, H. (2019). An approach to develop the smart health using Internet of Things and authentication based on biometric technology. Future Generation Computer Systems, 91, 434–449. https://doi.org/10.1016/j.future.2018.09.024
Hernandez-de-Menendez, M., Morales-Menendez, R., Escobar, C. A., & Arinez, J. (2021). Biometric applications in education. International Journal on Interactive Design and Manufacturing (IJIDeM), 15(2–3), 365–380. https://doi.org/10.1007/s12008-021-00760-6
Immersive Remote Collaboration and Workplace Tracking Systems, Mobile Biometric and Sentiment Data, and Algorithmic Monitoring and Wearable Augmented Reality Technologies in Generative Artificial Intelligence-based Virtual Human Resource Management. (2023). Contemporary Readings in Law and Social Justice, 15(2), 26. https://doi.org/10.22381/CRLSJ15220232
Iwasokun, G. B., Akinwonmi, A. E., & Bello, O. A. (2022). Baseline Study of COVID-19 and Biometric Technologies: International Journal of Sociotechnology and Knowledge Development, 14(1), 1–26. https://doi.org/10.4018/IJSKD.306232
Jung, Y. M. (2019). Data Analysis in Quantitative Research. In P. Liamputtong (Ed.), Handbook of Research Methods in Health Social Sciences (pp. 955–969). Springer Singapore. https://doi.org/10.1007/978-981-10-5251-4_109
Kearney, C. A., & Graczyk, P. A. (2020). A Multidimensional, Multi-tiered System of Supports Model to Promote School Attendance and Address School Absenteeism. Clinical Child and Family Psychology Review, 23(3), 316–337. https://doi.org/10.1007/s10567-020-00317-1
Lamin, N. Z., Jusoh, W. N. A. W., Zainudin, J., & Samad, H. (2021). Implementing Student Attendance System Using Fingerprint Biometrics for Kolej Universiti Poly-Tech Mara. IOP Conference Series: Materials Science and Engineering, 1062(1), 012037. https://doi.org/10.1088/1757-899X/1062/1/012037
Malatji, W. R., Zuva, T., & Van Eck, R. (2021). Acceptance of Biometric Authentication Security Technology on Mobile Devices. In V. Bindhu, J. M. R. S. Tavares, A.-A. A. Boulogeorgos, & C. Vuppalapati (Eds.), International Conference on Communication, Computing and Electronics Systems (Vol. 733, pp. 145–156). Springer Singapore. https://doi.org/10.1007/978-981-33-4909-4_11
Manta, C., Jain, S. S., Coravos, A., Mendelsohn, D., & Izmailova, E. S. (2020). An Evaluation of Biometric Monitoring Technologies for Vital Signs in the Era of COVID?19. Clinical and Translational Science, 13(6), 1034–1044. https://doi.org/10.1111/cts.12874
May, F., Ford, T., Janssens, A., Newlove?Delgado, T., Emma Russell, A., Salim, J., Ukoumunne, O. C., & Hayes, R. (2021). Attainment, attendance, and school difficulties in UK primary schoolchildren with probable ADHD. British Journal of Educational Psychology, 91(1), 442–462. https://doi.org/10.1111/bjep.12375
Negri, N. A. R., Borille, G. M. R., & Falcão, V. A. (2019). Acceptance of biometric technology in airport check-in. Journal of Air Transport Management, 81, 101720. https://doi.org/10.1016/j.jairtraman.2019.101720
Peng, Z., He, J., Yang, F., & Zhao, X. (2022). An Overview and Forecast of Biometric Recognition Technology Used in Forensic Science. In W. Deng, J. Feng, D. Huang, M. Kan, Z. Sun, F. Zheng, W. Wang, & Z. He (Eds.), Biometric Recognition (Vol. 13628, pp. 32–41). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-20233-9_4
Quinan, C. L., & Hunt, M. (2022). Biometric Bordering and Automatic Gender Recognition: Challenging Binary Gender Norms in Everyday Biometric Technologies. Communication, Culture and Critique, 15(2), 211–226. https://doi.org/10.1093/ccc/tcac013
Sepúlveda Carmona, M. (2019). Biometric technology and beneficiary rights in social protection programmes. International Social Security Review, 72(4), 3–28. https://doi.org/10.1111/issr.12219
Sharma, V., Dastidar, M. G., Sutradhar, S., Raj, V., De Silva, K., & Roy, S. (2022). A step toward better sample management of COVID-19: On-spot detection by biometric technology and artificial intelligence. In COVID-19 and the Sustainable Development Goals (pp. 349–380). Elsevier. https://doi.org/10.1016/B978-0-323-91307-2.00017-1
Southwest State University, Tomakova, I., Kopteva, Z., & Southwest State University. (2020). Integration of biometric technologies into a personnel management system in a digital economy. Economic Annals-??I, 186(11–12), 103–111. https://doi.org/10.21003/ea.V186-12
Vandana, & Kaur, N. (2022). Analytical Review of Biometric Technology Employing Vivid Modalities. International Journal of Image and Graphics, 22(01), 2250004. https://doi.org/10.1142/S0219467822500048
Yoshitoshi, M., & Takahashi, K. (2023). A critical analysis of court decision on mainstream school attendance of a child with medical care needs in Japan: A long way towards inclusive education. International Journal of Inclusive Education, 27(11), 1257–1271. https://doi.org/10.1080/13603116.2021.1888322
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