Muhammad Akbar Haikal Frasanta, D. Wijaya, Heru Nugroho, Tora Fahrudin
{"title":"Heart Diagnose Application Using Bagging Algorithm","authors":"Muhammad Akbar Haikal Frasanta, D. Wijaya, Heru Nugroho, Tora Fahrudin","doi":"10.1109/ICISIT54091.2022.9872984","DOIUrl":null,"url":null,"abstract":"One of the many organs in the human body is the heart. The function of the heart is to pump blood all over the body. If the heart is suffering damage or interference, it could cause many harms to people starting from chest pain, fatigue, dizziness, and the worse is death. To prevent this is by doing a heart health check to get the treatment needed. However, the patients have to come to the hospital to do a heart health check, which costs a lot of money. Therefore, we propose another method of diagnosing heart disease. This study uses a machine learning bagging algorithm (random forest) to detect heart disease with two classes: no disease or disease. The evaluation results show that the bagging algorithm achieved 97.8% accuracy from the best optimal grid search parameters. It can be concluded that this proposed method can fairly discriminate heart disease.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 1st International Conference on Information System & Information Technology (ICISIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISIT54091.2022.9872984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the many organs in the human body is the heart. The function of the heart is to pump blood all over the body. If the heart is suffering damage or interference, it could cause many harms to people starting from chest pain, fatigue, dizziness, and the worse is death. To prevent this is by doing a heart health check to get the treatment needed. However, the patients have to come to the hospital to do a heart health check, which costs a lot of money. Therefore, we propose another method of diagnosing heart disease. This study uses a machine learning bagging algorithm (random forest) to detect heart disease with two classes: no disease or disease. The evaluation results show that the bagging algorithm achieved 97.8% accuracy from the best optimal grid search parameters. It can be concluded that this proposed method can fairly discriminate heart disease.