IMPLEMENTASI FACE RECOGNITION PADA SISTEM ABSENSI MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN)

ARDIANSYAH, MUHAMMAD IRDAM (2024) IMPLEMENTASI FACE RECOGNITION PADA SISTEM ABSENSI MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN). S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

In this modern era, managing employee presence has become crucial to the productivity and operational management of the company. In order to improve efficiency and security, the use of face recognition technology has become a popular choice. The research aims to design and implement an absence system that uses facial recognition technology. using the Convolutional Neural Network (CNN) algorithm at Mili Coffee & Roastery. The research methodology focuses on the analysis of system needs, system architecture design, development of CNN algorithms, user interface design, as well as system integration plans. During this study, collected data on employee facial images, implemented CNN algoritms for facial recognition, system testing, this research is expected to contribute to the field of information technology especially in the development of effective and reliable absence systems. Keywords: Face Recognition, Convolutional Neural Network (CNN), Absence, Presence Management, Information Technology, System Design. Pada era modern ini, manajemen kehadiran karyawan menjadi krusial bagi produktivitas dan manajemen operasional perusahaan. Dalam rangka meningkatkan efisiensi dan keamanan, penggunaan teknologi face recognition telah menjadi pilihan populer. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem absensi yang menggunakan teknologi pengenalan wajah. menggunakan Algoritma Convolutional Neural Network (CNN) di Mili Coffee & Roastery. Metodologi penelitian berfokus pada analisis kebutuhan sistem, perancangan arsitektur sistem, pengembangan algoritma CNN, desain antarmuka pengguna, serta rencana integrasi sistem. Selama penelitian ini, dilakukan pengumpulan data citra wajah karyawan, implementasi algoritma CNN untuk pengenalan wajah, pengujian sistem, Penelitian ini diharapkan memberikan kontribusi pada bidang teknologi informasi terutama dalam pengembangan sistem absensi yang efektif dan handal. Kata kunci: Face Recognition, Convolutional Neural Network (CNN), Absensi, Manajemen Kehadiran, Teknologi Informasi, Perancangan Sistem.

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 24 140
Call Number:	SIK/15/24/102
NIM/NIDN Creators:	41520110093
Uncontrolled Keywords:	Face Recognition, Convolutional Neural Network (CNN), Absensi, Manajemen Kehadiran, Teknologi Informasi, Perancangan Sistem.
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 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 > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.32 Neural Nets (Neural Network)/Jaringan Saraf Buatan 100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 153 Conscious Mental Process and Intelligence/Intelegensia, Kecerdasan Proses Intelektual dan Mental > 153.1 Memory and Learning/Memori dan Pembelajaran > 153.12 Memory/Memori > 153.124 Recognition/Pengenalan 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma 600 Technology/Teknologi > 600. Technology/Teknologi
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	13 Aug 2024 05:26
Last Modified:	13 Aug 2024 05:26
URI:	http://repository.mercubuana.ac.id/id/eprint/90193

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