DETEKSI DINI PENYAKIT DIABETES MELITUS MENGGUNAKAN METODE NAIVE BAYES
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
HARJIMAN, NAUFAL ARISSAPUTRA
Indrianto, Indrianto
Sudirman, M. Yoga Distra
Indrianto, Indrianto
Sudirman, M. Yoga Distra
Subject
Teknik Informatika
Datestamp
2023-05-31 06:59:08
Abstract :
Diabetes is a chronic disease caused by a lack of insulin production (a hormone produced by the pancreas to regulate glucose levels) in the human body. If diabetes is not controlled properly, it can cause various complications that endanger the lives of sufferers. According to a survey by the World Health Organization (WHO), Indonesia ranks 4th in terms of the total population. Therefore, health workers need a system that can facilitate and assist the first handling of early detection of diabetes mellitus. Web-based applications have been developed for early detection of diabetes melitus. In handling the early detection of diabetes melitus requires making the right decisions so that the Naive Bayes method is needed to help the system deal with data uncertainty. In this study, an Early Detection system for diabetes melitus was created which can assist health workers in carrying out early detection of diabetes melitus and provide advice in the form of early treatment to users. The result of this study is an early detection of diabetes melitus to detect whether the user suffers from diabetes melitus or not. The Gaussian model of the Naive Bayes method applied in this application has an accuracy rate of 85%.
Diabetes is a chronic disease caused by a lack of insulin production (a hormone produced by the pancreas to regulate glucose levels) in the human body. If diabetes is not controlled properly, it can cause various complications that endanger the lives of sufferers. According to a survey by the World Health Organization (WHO), Indonesia ranks 4th in terms of the total population. Therefore, health workers need a system that can facilitate and assist the first handling of early detection of diabetes mellitus. Web-based applications have been developed for early detection of diabetes melitus. In handling the early detection of diabetes melitus requires making the right decisions so that the Naive Bayes method is needed to help the system deal with data uncertainty. In this study, an Early Detection system for diabetes melitus was created which can assist health workers in carrying out early detection of diabetes melitus and provide advice in the form of early treatment to users. The result of this study is an early detection of diabetes melitus to detect whether the user suffers from diabetes melitus or not. The Gaussian model of the Naive Bayes method applied in this application has an accuracy rate of 85%.
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