Students’ Number Detection System Using Internet of Things (IoT) Based on Image Classification Method

Authors

  • Buhari Buhari STKIP Harapan Bima
  • Muslimin Muslimin STKIP Harapan Bima
  • Lisda Ramdhani STKIP Harapan Bima

DOI:

https://doi.org/10.58258/jupe.v10i3.9483

Keywords:

Student number detection system using internet-based image classification method Internet Of Things (IoT).

Abstract

This research aims to develop a system that can provide classroom security, design and implement a student facial recognition system in classrooms. The development of a student counting system using IoT-based image classification methods makes it easier for lecturers and teachers to document student numbers. This research uses a campus or school classroom as the case study location.The devices used include a camera or webcam module as a face detection input device, a laptop to process the camera input, validate it against the class database, and perform the identification process (using the image classification library in the OpenCV application), and a laptop that functions as a web server to display the student count dashboard page. Test results show that the system can function properly when the distance between the camera and the student's face is between 30 cm and 170 cm, and cannot count at all at a distance of 180 cm. 

References

Akmal. 2019. Lebih Dekat Dengan Industri 4.0. Yogyakarta: Deepublish (Group Penerbitan CV Budi Utama)

Ekojono., dkk. 2018. Pemrograman Spreadsheet Untuk Pemodelan Kontrol Rangkaian Elektronik. Malang :Polinema Press

Gollmann, D. (2011). Computer Security Wiley.

Hafizah, E. N., & Muna, K. (2024). Identification of Learning Resource Access in Improving Students’ Knowledge in Linguistic At MIN 3 Tapin. Journal of Educational Research and Practice, 2(1), 11–29.

Hamdai., Andi Wawan Indrawan. 2015. Programmable Logic Controller Dan Scada Teori, Pemrograman dan Aplikasinya Dalam Otomasi Sistem Tanur. Yogyakarta: Deepublish (Group Penerbitan CV Budi Utama)

Jogiyanto Hartono (2005) Engineering. Yogyakarta: Deepublish (Group Penerbitan CV Budi Utama)

Mishra, A. (2011). Security and Intrusion Detection in Wireless Networks. Springer.

Orlando, W. Kasoep, and D. Yolanda, “Sistem Monitoring dan Penjernihan Air Berdasarkan Derajat Keasaman (PH) dan Kekeruhan Pada Bak Penampungan Air Berbasis Internet of Things,” J. Comput. Hardware, Signal Proscessing, Embed. Syst. Netw., vol. 01, no. 01, pp. 17–22, 2020.

O’Brien (2005) “Sistem Sistem Keamanan Ruangan, Studi Kasus Ruang Server Perguruan Tinggi Raharja.

Prayogo, R. Alfita, and K. A. Wibisono, “Sistem Monitoring Denyut Jantung Dan Suhu Tubuh Sebagai Indikator Level Kesehatan Pasien Berbasis Iot (Internet Of Thing) Dengan Metode Fuzzy Logic.

Susanto, F., Rifai, M.N., & Fanisa, A. 2017. Internet Of Things Pada Sistem Keamanan Ruangan, Studi Kasus Ruang Server Perguruan Tinggi Raharja. Semnasteknomedia, 5(1), 1-6.

Widiasari, P. Insani, and M. Diono, “Sistem Monitoring Tangki dan Penghitung RunHour Genset Otomatis Berbasis Internet of Things ( IoT ),” J. Politek. Caltex Riau, vol. 5, no. 2, pp. 59–70, 2019.

Scarfone, K., & Mell, P. (2007). Guide to Intrusion Detection and Prevention Systems (IDPS). NIST Special Publication 800-94

Yurindra. 2017. Software Engineering. Yogyakarta: Deepublish (Group Penerbitan CV Budi Utama)

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Published

2025-09-27

How to Cite

Students’ Number Detection System Using Internet of Things (IoT) Based on Image Classification Method. (2025). JUPE : Jurnal Pendidikan Mandala, 10(3), 1283-1289. https://doi.org/10.58258/jupe.v10i3.9483