Tata Sutabri, Tata Sutabri and Pamungkur, Pamungkur and Ade Kurniawan, Ade Kurniawan and Raymond Erz Saragih, Raymond Erz Saragih (2019) Automatic Attendance System for University Student Using Face Recognition Based on Deep Learning. International Journal of Machine Learning and Computing, 9 (5). pp. 668-674. ISSN 2010-3700
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Abstract
Student attendance is essential in the learning process. To record student attendance, several ways can be done; one of them is through student signatures. The process has several shortcomings, such as requiring a long time to make attendance; the attendance paper is lost, the administration must enter attendance data one by one into the computer. To overcome this, the paper proposed a web-based student attendance system that uses face recognition. In the proposed system, Convolutional Neural Network (CNN) is used to detect faces in images, deep metric learning is used to produce facial embedding, and K-NN is used to classify student's faces. Thus, the computer can recognize faces. From the experiments conducted, the system was able to recognize the faces of students who did attend and their attendance data was automatically saved. Thus, the university
| Item Type: | Article |
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| Subjects: | Q Science > Q Science (General) |
| Depositing User: | Dr. Tata Sutabri |
| Date Deposited: | 30 Mar 2023 00:40 |
| Last Modified: | 30 Mar 2023 00:40 |
| URI: | http://eprints.binadarma.ac.id/id/eprint/17400 |
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