{"title":"智能家庭授权的安全系统使用o输入库中的面部识别","authors":"Moh Eki Riyadani, S. Subiyanto","doi":"10.47970/siskom-kb.v5i2.284","DOIUrl":null,"url":null,"abstract":"As industrial 4.0 advances such as Internet of Things (IoT), Big Data, Cloud Computing , and Artificial Intelligent (AI) has prompted reseachers to innovate in various fields, including security systems. The security system is an important issue due to rise of theft in a residence. A security system is needed for home authorizon to prevent the crime of theft. Security systems are built using facial recognition. The research proposes to develop a security system using facial recognition based Raspberry Pi with Python programming and utilize the OpenCV. System testing includes training function testing, facial recognition function, image delevery function, decision-making function, and system performance testing, system performance for facial recognition is calculated using confusion matrix formula that produces 100% sensitivity, 13% specitificity, and 97% accuracy. \n ","PeriodicalId":104889,"journal":{"name":"Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sistem Keamanan Untuk Otorisasi Pada Smart Home Menggunakan Pengenalan Wajah Dengan Library OpenCV\",\"authors\":\"Moh Eki Riyadani, S. Subiyanto\",\"doi\":\"10.47970/siskom-kb.v5i2.284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As industrial 4.0 advances such as Internet of Things (IoT), Big Data, Cloud Computing , and Artificial Intelligent (AI) has prompted reseachers to innovate in various fields, including security systems. The security system is an important issue due to rise of theft in a residence. A security system is needed for home authorizon to prevent the crime of theft. Security systems are built using facial recognition. The research proposes to develop a security system using facial recognition based Raspberry Pi with Python programming and utilize the OpenCV. System testing includes training function testing, facial recognition function, image delevery function, decision-making function, and system performance testing, system performance for facial recognition is calculated using confusion matrix formula that produces 100% sensitivity, 13% specitificity, and 97% accuracy. \\n \",\"PeriodicalId\":104889,\"journal\":{\"name\":\"Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47970/siskom-kb.v5i2.284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47970/siskom-kb.v5i2.284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sistem Keamanan Untuk Otorisasi Pada Smart Home Menggunakan Pengenalan Wajah Dengan Library OpenCV
As industrial 4.0 advances such as Internet of Things (IoT), Big Data, Cloud Computing , and Artificial Intelligent (AI) has prompted reseachers to innovate in various fields, including security systems. The security system is an important issue due to rise of theft in a residence. A security system is needed for home authorizon to prevent the crime of theft. Security systems are built using facial recognition. The research proposes to develop a security system using facial recognition based Raspberry Pi with Python programming and utilize the OpenCV. System testing includes training function testing, facial recognition function, image delevery function, decision-making function, and system performance testing, system performance for facial recognition is calculated using confusion matrix formula that produces 100% sensitivity, 13% specitificity, and 97% accuracy.