Sistem Presensi Mahasiswa Menggunakan Face Recognition Dengan Metode Facenet Pada Android

Evelyn Evelyn(1*), Rudy Adipranata(2), Kartika Gunadi(3),

(1) Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
(2) Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
(3) Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
(*) Corresponding Author


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.


attendance system; facial recognition; Facenet; L2Norm; Cosine Similarity; Cloud Firestore

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Asy’Ari, M. Z. (2020, November 13). Apa itu tensorflow? 3

Hal Penting Untuk Dipahami. Auftechnique.

Bah, S. M., & Ming, F. (2020). An improved face recognition

algorithm and its application in attendance management

system. An Improved Face Recognition Algorithm and Its

Application in Attendance Management System, 5, 100014.

Craig, C., & Gerber, A. (2015). Learn Android Studio : Build

Android Apps Quickly and Effectively. New York: Apress.

Google. (2019). Cloud Firestore | Firebase Documentation.


Google. (2020). ML Kit for Firebase. Firebase.

Google. (2020). Ringkasan CameraX. Android Developers.

Heiss, J. J. (2015, April). The Advent of Kotlin: A

Conversation with JetBrains' Andrey Breslav. Diambil

kembali dari Java:

Putra, W. S. E. (2016). Klasifikasi Citra Menggunakan

Convolutional Neural Network (CNN) pada Caltech 101.

Jurnal Teknik ITS, 5(1).

Sunaryono, D., Siswantoro, J., & Anggoro, R. (2019). An

android based course attendance system using face

recognition. Journal of KingSaud University.


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