APLIKASI ABSENSI TEST PSIKOTEST PT.INDOSAT BEDASARKAN PENGENALAN WAJAH MENGGUNAKAN METODE PINCIPAL COMPONENT ANALYSIS

MUHLIS, MUHLIS (2021) APLIKASI ABSENSI TEST PSIKOTEST PT.INDOSAT BEDASARKAN PENGENALAN WAJAH MENGGUNAKAN METODE PINCIPAL COMPONENT ANALYSIS. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Attendance lists are used by schools and companies to control attendance. Nowadays there are so many attendance methods that have been applied with manual methods such as signatures or calling names. Manual attendance system which is still simple has weaknesses that can be easily manipulated. A person's signature can be forged, while a name can be represented by someone else. With the development of technology at this very rapid rate, it is expected to solve the problem by using technology such as using face recognition. Face recognition is one of the biometric technologies used to detect and identify faces. This face recognition application uses a camera to capture a person's face and compare it with a specific database. This application of attendance is a desktop-based application using Linear Discriminant Analysis method with C# language. This method is good for extracting facial features using Eigenface Algorithm. Based on the experimental processes conducted it can be concluded that the success rate of facial recognition average is 73%. Keywords: face recognition, Psycho test attendance, Principal Component Analysis (PCA) Penggunaan absensi konvensional digunakan oleh sekolah dan perusahaan untuk mengontrol kehadiran seseorang. Metode ini dengan cara memanggil nama atau mengisi list tanda tangan. Hanya saja metode ini memiliki kelemahan dan dapat dimanipulasi. Penggunaan face recognition dapat menghindari kelemahan tersebut. Face recognition adalah salah satu dari teknologi biometrik yang digunakan untuk mendeteksi dan mengidentifikasi wajah. Aplikasi pengenalan wajah ini menggunakan sebuah kamera untuk menangkap wajah seseorang dan dibandingkan dengan database tertentu. Aplikasi absensi ini berbasis dekstop menggunakan bahasa C# dengan metode Principal Component Analysis (PCA). Metode ini melakukan ekstraksi fitur wajah menggunakan Algoritma Eigenface. Berdasarkan proses uji coba yang dilakukan dapat disimpulkan bahwa tingkat akurasi sebesar 73%. Kata Kunci: pengenalan wajah, Absensi psikotes, Principal Component Analysis (PCA).

Item Type:	Thesis (S1)
NIM/NIDN Creators:	41817110143
Uncontrolled Keywords:	pengenalan wajah, Absensi psikotes, Principal Component Analysis (PCA).
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data > 005.5 General Purpose Application Programs/Program Aplikasi dengan Kegunaan Khusus 600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 651 Office Services/Layanan Kantor 600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 651 Office Services/Layanan Kantor > 651.8 Computer Application for Office Management/Aplikasi Komputer untuk Manajemen Perkantoran 600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data] > 658.05 Data Processing Computer Applications/Pengolahan Data Aplikasi Komputer
Divisions:	Fakultas Ilmu Komputer > Sistem Informasi
Depositing User:	Dede Muksin Lubis
Date Deposited:	27 Mar 2023 03:32
Last Modified:	27 Mar 2023 03:32
URI:	http://repository.mercubuana.ac.id/id/eprint/75517

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