SISTEM KEAMANAN PINTU DENGAN PENGENALAN WAJAH MENGGUNAKAN METODE FEATURE EXTRACTION BERBASIS RASPBERRY PI 3

Avianto, Alvintri (2019) SISTEM KEAMANAN PINTU DENGAN PENGENALAN WAJAH MENGGUNAKAN METODE FEATURE EXTRACTION BERBASIS RASPBERRY PI 3. Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

Security is very important for every home to keep valuable assets in the house. A key is one of the safeguards that is always used, but because of the density of activity it causes a person to forget to bring or pull the key that is on the door and it will certainly be inconvenient for the homeowner. To overcome this problem in this final project a door security system that uses face detection is built so that homeowners no longer need a conventional key. This system uses a raspberry pi 3 as a microcontroller and the image will be processed using the feature extraction method. The image matching results captured by the webcam will activate the relay and then activate the solenoid door lock. When the system works properly the buzzer and LED will light as an indicator of the success of the system. In addition, this final project aims to compare the feature extraction method with the principal component analysis method that has been published in the Journal of Telecommunications Engineering Study Program Sriwijaya State Polytechnic Electrical Engineering in the article entitled "Home security with Face Recognition System in Real Time Using Principal Component Analysis Method ". The accuracy of detection using the feature extraction method has an average success rate of 100% and the average accuracy using the principal component analysis method has an average rate of 88%. Keywords: Face Detection, Raspberry Pi 3, Feature Extraction, Solenoid Door Lock, Principal Component Analysis

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Fakultas Teknologi Informasi dan Elektro > S1 Teknik Elektro
Depositing User: UTY MS Hendriyawan Achmad
Date Deposited: 18 Oct 2019 06:44
Last Modified: 18 Oct 2019 06:44
URI: http://eprints.uty.ac.id/id/eprint/3504

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