{"title":"使用定制的神经握手识别系统","authors":"L. Putra, Eka Kusumawardhani, Putranty Widha Nugraheni, Lalak Tarbiyatun Nasyin Maleiva, Vincentius Abdi Gunawan","doi":"10.47111/jti.v16i2.5096","DOIUrl":null,"url":null,"abstract":"Heart disease is a disease with the second-highest mortality rate in the world. This happens because of an unhealthy human lifestyle. This unhealthy lifestyle affects the performance of the body's organs in carrying out their functions. Stroke can be prevented by exercising regularly, eating nutritious foods, not consuming alcohol, and not consuming tobacco. One way to find out if someone is free from stroke or not can be done by medical check-ups. However, this method is quite expensive. Given these problems, this study aims to design an early identification system for detecting early-stage stroke. The system is designed by utilizing the condition and history of the subject for identification. This study uses a back propagation neural network for the classification process. Variations in the use of hidden layers in each experiment were used to obtain the highest accuracy in the training process. From the results of the study, it was found that the system designed can detect early stroke with an accuracy rate of 97.8%.","PeriodicalId":214711,"journal":{"name":"Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SISTEM IDENTIFIKASI DINI PENYAKIT STROKE DENGAN MENGGUNAKAN JARINGAN SYARAF TIRUAN PERAMBATAN BALIK\",\"authors\":\"L. Putra, Eka Kusumawardhani, Putranty Widha Nugraheni, Lalak Tarbiyatun Nasyin Maleiva, Vincentius Abdi Gunawan\",\"doi\":\"10.47111/jti.v16i2.5096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heart disease is a disease with the second-highest mortality rate in the world. This happens because of an unhealthy human lifestyle. This unhealthy lifestyle affects the performance of the body's organs in carrying out their functions. Stroke can be prevented by exercising regularly, eating nutritious foods, not consuming alcohol, and not consuming tobacco. One way to find out if someone is free from stroke or not can be done by medical check-ups. However, this method is quite expensive. Given these problems, this study aims to design an early identification system for detecting early-stage stroke. The system is designed by utilizing the condition and history of the subject for identification. This study uses a back propagation neural network for the classification process. Variations in the use of hidden layers in each experiment were used to obtain the highest accuracy in the training process. From the results of the study, it was found that the system designed can detect early stroke with an accuracy rate of 97.8%.\",\"PeriodicalId\":214711,\"journal\":{\"name\":\"Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika\",\"volume\":\"89 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47111/jti.v16i2.5096\",\"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 Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47111/jti.v16i2.5096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SISTEM IDENTIFIKASI DINI PENYAKIT STROKE DENGAN MENGGUNAKAN JARINGAN SYARAF TIRUAN PERAMBATAN BALIK
Heart disease is a disease with the second-highest mortality rate in the world. This happens because of an unhealthy human lifestyle. This unhealthy lifestyle affects the performance of the body's organs in carrying out their functions. Stroke can be prevented by exercising regularly, eating nutritious foods, not consuming alcohol, and not consuming tobacco. One way to find out if someone is free from stroke or not can be done by medical check-ups. However, this method is quite expensive. Given these problems, this study aims to design an early identification system for detecting early-stage stroke. The system is designed by utilizing the condition and history of the subject for identification. This study uses a back propagation neural network for the classification process. Variations in the use of hidden layers in each experiment were used to obtain the highest accuracy in the training process. From the results of the study, it was found that the system designed can detect early stroke with an accuracy rate of 97.8%.