Sistem Presensi Mahasiswa Menggunakan Face Recognition Dengan Metode Facenet Pada Android
Abstract
As of today, the student attendance system in the University of Petra uses a QR code system to do their daily attendance. This QR code system has some flaws that are often exploited by the students. Students usually exploit this system by asking their peers to login into their accounts and take the attendance for them by scanning the shared QR code. Implementing face recognition can be one of the means of prevention. This attendance system is an Android based system using Facenet model for the facial recognition system. Formulas L2Norm and Cosine Similarity is used for comparison means for the results of the face recognition system. Results show that cosine similarity is most optimal when using the 0.5f threshold with the score of 0.5104218 and accuracy with the score of 0.77162087. Meanwhile, L2Norm results show that it is most optimal when using the 8.0f threshold with the score of 5.8973804 and accuracy with the score of 5.8973804.References
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