{"title":"OPTIMASI ALGORITMA C4.5 MENGGUNAKAN ALGORITMA GENETIKA UNTUK PREDIKSI PENYAKIT HEPATITIS","authors":"Wisti Dwi Septiani","doi":"10.33480/INTI.V15I1.1421","DOIUrl":null,"url":null,"abstract":"Hepatitis is an infectious disease which is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Hepatitis is inflammation of the liver that can increase into liver cancer. The most common causes of hepatitis are those caused by hepatitis B and C viruses. Previous research used the data mining classification method C.45 algorithm and showed an accuracy rate of 77.29%. The purpose of this study is to improve the accuracy of the C.45 algorithm by optimization using genetic algorithm. The results of this further research are the decision tree and an increase in the accuracy rate of 12.42% from 77.29% to 89.71%.","PeriodicalId":197142,"journal":{"name":"INTI Nusa Mandiri","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTI Nusa Mandiri","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33480/INTI.V15I1.1421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Hepatitis is an infectious disease which is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Hepatitis is inflammation of the liver that can increase into liver cancer. The most common causes of hepatitis are those caused by hepatitis B and C viruses. Previous research used the data mining classification method C.45 algorithm and showed an accuracy rate of 77.29%. The purpose of this study is to improve the accuracy of the C.45 algorithm by optimization using genetic algorithm. The results of this further research are the decision tree and an increase in the accuracy rate of 12.42% from 77.29% to 89.71%.
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