Rifqi Hammad, Julia Kurniasih, N. Hasan, Christin Nandari Dengen, Kusrini Kusrini
{"title":"Prototipe Machine Learning Untuk Prognosis Penyakit Demensia (The Prototype of Machine Learning for The Prognosis of Dementia)","authors":"Rifqi Hammad, Julia Kurniasih, N. Hasan, Christin Nandari Dengen, Kusrini Kusrini","doi":"10.33164/iptekkom.21.1.2019.17-29","DOIUrl":null,"url":null,"abstract":"Alzheimer's Disease International estimates that the number of people living with dementia in Indonesia is estimated to increase to more than 2 million by 2030. The loss suffered by Indonesia due to dementia is projected to reach US $ 1.7 billion per year. This is due to a decrease in cognitive function and social activities experienced by people with dementia . As a result, public health problems arise, which have an impact on increasing health costs. To address this issue, proper handling is needed. The development of assistive technologies for prognosis of dementia may support the treatment process better. This study developed a machine learning prototype for the prognosis of dementia using rule-based forward chaining method. The results showed an accuracy value of 100%, which suggested that the prognosis has complied with the expert rules.","PeriodicalId":368220,"journal":{"name":"JURNAL IPTEKKOM : Jurnal Ilmu Pengetahuan & Teknologi Informasi","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JURNAL IPTEKKOM : Jurnal Ilmu Pengetahuan & Teknologi Informasi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33164/iptekkom.21.1.2019.17-29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Alzheimer's Disease International estimates that the number of people living with dementia in Indonesia is estimated to increase to more than 2 million by 2030. The loss suffered by Indonesia due to dementia is projected to reach US $ 1.7 billion per year. This is due to a decrease in cognitive function and social activities experienced by people with dementia . As a result, public health problems arise, which have an impact on increasing health costs. To address this issue, proper handling is needed. The development of assistive technologies for prognosis of dementia may support the treatment process better. This study developed a machine learning prototype for the prognosis of dementia using rule-based forward chaining method. The results showed an accuracy value of 100%, which suggested that the prognosis has complied with the expert rules.