Design and Development of Student Attention System using Face Recognition Based on MTCNN and FaceNet

Authors

  • Moch. Maulana Andhika Candra Digital Telecommunication Network Study Program, Department of Electrical Engineering, State Polytechnic of Malang, 65141, Indonesia
  • Hudiono Hudino Digital Telecommunication Network Study Program, Department of Electrical Engineering, State Polytechnic of Malang, 65141, Indonesia
  • Yoyok Heru Prasetyo Isnomo Digital Telecommunication Network Study Program, Department of Electrical Engineering, State Polytechnic of Malang, 65141, Indonesia

Keywords:

Attendance system, FaceNet, IP Camera, MTCNN

Abstract

Employees use their level of attendance or absence to demonstrate their presence at work or absence from it in an agency. This absence is connected to how discipline is applied, which is decided by each organization or institution. It can be inferred from this that student absenteeism in a setting where there is activity serves to increase discipline and demonstrate attendance. With IP Camera technology, it can be applied to the attendance system using the MTCNN method as face detection and FaceNet to extract high-quality features from the face. The system created can detect faces at a distance of 40 cm – 180 cm with an accuracy of 90.5% and can detect more than 1 object in 1 frame so that the IP Camera function is in accordance with the design in real-time. Tested the object of 3 pairs of twin faces produces a maximum accuracy of 90% where the level of match between the faces and the data is appropriate.

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Published

2023-09-19

How to Cite

[1]
M. M. A. Candra, H. Hudino, and Y. H. P. Isnomo, “Design and Development of Student Attention System using Face Recognition Based on MTCNN and FaceNet”, Jartel, vol. 13, no. 3, pp. 225-231, Sep. 2023.