Universitas Negeri Semarang, Indonesia
BibTex Citation Data :
@article{JTSISKOM13590, author = {Subiyanto Subiyanto and Dina Priliyana and Moh. Eki Riyadani and Nur Iksan and Hari Wibawanto}, title = {Sistem pengenalan wajah dengan algoritme PCA-GA untuk keamanan pintu rumah pintar menggunakan Rasberry Pi}, journal = {Jurnal Teknologi dan Sistem Komputer}, volume = {8}, number = {3}, year = {2020}, keywords = {face recognition; genetic algorithm; principal component analysis; raspberry pi; smart home system}, 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.}, issn = {2338-0403}, pages = {210--216} doi = {10.14710/jtsiskom.2020.13590}, url = {https://jtsiskom.undip.ac.id/article/view/13590} }
Refworks Citation Data :
Article Metrics:
Last update:
Hybrid of DCT And PCA For Image Size Compression
Application of portrait recognition system for emergency evacuation in mass emergencies
Prototype of Iot-Based Keyless Security System For Motorcycle
Last update: 2024-11-18 11:16:40
IoT and Sign Language System (SLS)
Starting from 2021, the author(s) whose article is published in the JTSiskom journal attain the copyright for their article and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. By submitting the manuscript to JTSiskom, the author(s) agree with this policy. No special document approval is required.
The author(s) guarantee that:
The author(s) retain all rights to the published work, such as (but not limited to) the following rights:
Suppose the article was prepared jointly by more than one author. Each author submitting the manuscript warrants that all co-authors have given their permission to agree to copyright and license notices (agreements) on their behalf and notify co-authors of the terms of this policy. JTSiskom will not be held responsible for anything arising because of the writer's internal dispute. JTSiskom will only communicate with correspondence authors.
Authors should also understand that their articles (and any additional files, including data sets and analysis/computation data) will become publicly available once published. The license of published articles (and additional data) will be governed by a Creative Commons Attribution-ShareAlike 4.0 International License. JTSiskom allows users to copy, distribute, display and perform work under license. Users need to attribute the author(s) and JTSiskom to distribute works in journals and other publication media. Unless otherwise stated, the author(s) is a public entity as soon as the article is published.