SAPUTRA, ALFEUS ADI (2022) IMPLEMENTASI FACE RECOGNITION PADA SISTEM ABSENSI BERBASIS ANDROID MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) DAN LOCK GPS. S1 thesis, Universitas Mercu Buana.
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Abstract
Technological growth is developing very rapidly in various sectors, ranging from industry, offices, government to education. Implementation of Face Recognition on the Android-based employee attendance system is used to perform attendance by scanning the face using Android in certain areas (offices/companies), so there is no need to use manual attendance or finger print which will result in queues when doing attendance. The attendance system in some companies is still done manually by filling out an attendance book or using a finger print. Attendance manually or using fingerprints will certainly result in queues if employees come at the same time this is certainly less effective. To deal with this problem, an Android-based attendance application that uses face recognition technology is needed, where the application can only be accessed in the office environment (range area). This study uses the Convolutional Neural Network (CNN) algorithm which will be used for image processing, besides that this study also uses the GPS Lock method which will be used to determine the presence area/coverage. The dataset used in the study was facial images of 10 people, each individual sampled as many as 50 images. The results of this study will make the attendance system more effective, as well as simplify the attendance process and also avoid queues. Key words: Attendance , Convolutional Neural Network (CNN), Employee, Face Recognition, Lock GPS Pertumbuhan teknologi berkembang sangat cepat di berbagai sektor, mulai dari industri, perkantoran, pemerintahan hingga pendidikan. Implementasi Face Recognition pada sistem absensi karyawan berbasis android digunakan untuk melakukan absensi dengan cara memindai wajah menggunakan android di area tertentu (kantor/perusahaan), sehingga tidak perlu lagi menggunakan absensi manual ataupun dengan finger print yang akan mengakibatkan antrian pada saat melakukan absensi. Sistem absensi pada beberapa perusahaan masih dilakukan secara manual dengan cara mengisi buku kehadiran atau menggunakan finger print. Absensi dengan cara manual ataupun menggunakan fingerprint tentu akan akan mengakibatkan antrian jika karyawan datang secara bersamaan hal ini tentu kurang efektif. Untuk menangani masalah tersebut diperlukan aplikasi absensi berbasis android yang menggunakan teknologi face recognition, dimana aplikasi tersebut hanya bisa di akses di lingkungan kantor (range area). Penelitian ini menggunakan algoritma Convolutional Neural Network (CNN) yang akan digunakan untuk pengolahan citra, selain itu penelitian ini juga menggunakan metode Lock GPS yang akan digunakan untuk menentukan area/cakupan presensi. Dataset yang digunakan dalam penelitian berupa citra wajah dari 10 orang, setiap individu diambil sampel sebanyak 50 gambar. Hasil dari penelitian ini akan membuat sistem absensi lebih efektif, serta mempermudah proses absensi dan juga menghindari terjadinya antrian. Kata kunci: Convolutional Neural Network (CNN), Face Recognition, Karyawan, Lock GPS, Presensi
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