PEMBUATAN APLIKASI PENGENALAN WAJAH UNTUK SISTEM PRESENSI KELAS MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK
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Abstract
Abstract—Attendance is a method used by an agency to record workers who work in an agency or students who are in an educational agency. During the pandemic, the University of Surabaya changed the attendance system it used, the system first used before the pandemic was paper, during the pandemic the University of Surabaya changed the attendance system to use a website. On this website, students only need to select courses that are currently in progress and carry out the attendance process. In 2022 the Indonesian government will allow universities and schools to carry out face-to-face learning processes. The University of Surabaya is also making a transition from online to face-to-face learning, however the attendance system used is still a website, this causes students to have fictitious attendance or make attendance but students do not attend class. Based on these problems, this research created an application that can help the university to prevent students from making fictitious attendance by using face recognition in the attendance process using the Convolutional Neural Network or CNN method. The process of creating a CNN model will use a pre-trained model, namely GoogleNet, which has 1 layer added and the Hyperparameter Tuning process will be used to get the best CNN model by looking for optimal Hyperparameter values based on the predetermined Hyperparameter values and types. One of the results of the CNN model making trial was that the best model was obtained with an accuracy rate of 97%.
Keywords: convolutional neural network, face recognition, attendance
Abstrak—Presensi merupakan sebuah metode yang digunakan oleh sebuah instansi untuk mencatat para pekerja yang bekerja di sebuah instansi tersebut atau para mahasiswa/i atau siswa/i yang berada di sebuah instansi pendidikan. Pada masa pandemi Universitas Surabaya mengubah sistem presensi yang digunakan, sistem yang pertama kali digunakan sebelum pandemi berupa kertas, saat pandemi Universitas Surabaya mengubah sistem presensi menggunakan website. Pada website ini mahasiswa hanya perlu memilih mata kuliah yang sedang berlangsung dan melakukan proses presensi. Pada tahun 2022 pemerintah Indonesia memperbolehkan Universitas serta Sekolah untuk melakukan proses pembelajaran secara tatap muka. Universitas Surabaya juga melakukan transisi dari pembelajaran online menjadi tatap muka, akan tetapi sistem presensi yang digunakan masih berupa website, hal ini menyebabkan mahasiswa presensi fiktif atau melakukan presensi namun mahasiswa tidak mengikuti kelas. Berdasarkan permasalahan tersebut pada penelitian ini dibuat sebuah aplikasi yang dapat membantu pihak universitas untuk mencegah mahasiswa melakukan presensi fiktif dengan digunakannya pengenalan wajah atau face recognition dalam proses presensi menggunakan metode Convolutional Neural Network atau CNN. Proses pembuatan model CNN akan digunakan model pre-trained yaitu GoogleNet yang ditambahkan 1 layer dan akan digunakan proses Hyperparameter Tuning untuk mendapatkan model CNN terbaik dengan mencari nilai Hyperparameter yang optimal berdasarkan nilai dan jenis Hyperparameter yang telah ditentukan. Salah satu hasil uji coba pembuatan model CNN didapatkan model terbaik dengan tingkat akurasi 97%.
Kata kunci: convolutional neural network, face recognition, presensi
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