Implementasi Fitur Face Recognition pada Sistem Pemilihan Ketua Umum UKKI dengan Menggunakan Algoritma Haar Cascade Classifier dan Convolutional Neural Networks

Purnomo, Andi (2024) Implementasi Fitur Face Recognition pada Sistem Pemilihan Ketua Umum UKKI dengan Menggunakan Algoritma Haar Cascade Classifier dan Convolutional Neural Networks. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

The General Election System is one of the effective means in an effort to elect a leader, but the system is quite prone to fraud, especially if it is increasingly massive in scope. Implementing face recognition features into the election system is expected to realize a LUBER JURDIL election system. UKM UKKI is used as a case study for this research by using a dataset of faces from UKKI members. Face Recognition is able to recognize a person with the implementation of appropriate visual computer algorithms. The algorithm used is the Haar Cascade Classifier algorithm supported by two CNN models, namely MTCNN and FaceNet to improve accuracy and detection process. The Haar Cascade Classifier algorithm plays a role in the initial detection and face capture process, while MTCNN plays a role in face extraction so that it can be verified and embedded easily by the FaceNet model. The implementation of the Haar Cascade Classifier algorithm and the two CNN models resulted in an accuracy value of 99.42% with a training time of 33 minutes 45 seconds and was able to be applied to the UKKI general chairman election system that runs on a web page by utilizing the Flask microframework as a basic component in making a web-based general chairman election system. Keywords: face recognition, Haar Cascade Classifier, MTCNN, FaceNet

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Aditiawan, Firza Prima	NIDN0023058605	firzaprima.if@upnjatim.ac.id
Thesis advisor	Sihananto, Andreas Nugroho	NIDN0012049005	andreas.nugroho.jarkom@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Q Science > QA Mathematics > QA76.6 Computer Programming
T Technology > T Technology (General)
T Technology > T Technology (General) > T385 Computer Graphics

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

Andi Andi Purnomo

Date Deposited:

15 Aug 2024 06:45

Last Modified:

15 Aug 2024 06:45

URI:

https://repository.upnjatim.ac.id/id/eprint/28244