Sistem pengenalan wajah dengan algoritme PCA-GA untuk keamanan pintu rumah pintar menggunakan Rasberry Pi

Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi

*Subiyanto Subiyanto orcid scopus  -  Universitas Negeri Semarang, Indonesia
Dina Priliyana  -  Universitas Negeri Semarang, Indonesia
Moh. Eki Riyadani  -  Universitas Negeri Semarang, Indonesia
Nur Iksan orcid scopus  -  Universitas Negeri Semarang, Indonesia
Hari Wibawanto orcid scopus  -  Universitas Negeri Semarang, Indonesia
Received: 12 Dec 2019; Revised: 18 May 2020; Accepted: 25 May 2020; Published: 31 Jul 2020; Available online: 7 Jun 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
License URL: http://creativecommons.org/licenses/by-sa/4.0

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Section: Original Research Articles
Language: ID
Statistics: 364 94
Abstract
Genetic algorithm (GA) can improve the classification of the face recognition process in the principal component analysis (PCA). However, the accuracy of this algorithm for the smart home security system has not been further analyzed. This paper presents the accuracy of face recognition using PCA-GA for the smart home security system on Raspberry Pi. PCA was used as the face recognition algorithm, while GA to improve the classification performance of face image search. The PCA-GA algorithm was implemented on the Raspberry Pi. If an authorized person accesses the door of the house, the relay circuit will unlock the door. The accuracy of the system was compared to other face recognition algorithms, namely LBPH-GA and PCA. The results show that PCA-GA face recognition has an accuracy of 90 %, while PCA and LBPH-GA have 80 % and 90 %, respectively.
Keywords: face recognition; genetic algorithm; principal component analysis; raspberry pi; smart home system

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