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M. Sabransyah
Mahasiswa Program Studi Statistika FMIPA Universitas Mulawarman

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Aplikasi Metode Naive Bayes dalam Prediksi Risiko Penyakit Jantung M. Sabransyah; Yuki Novia Nasution; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Classification is an activity for assessing object data which include it the data into particular class among any number of classes available. Naive Bayes is classification with probability method. This research examines the use of naive Bayes method for a heart disease risk prediction application. In this research, it will be classified a person who have the risk of heart disease by using the data of patient in RSUD AWS during November and December 2016 the sample case is 47 years old male object, has cholesterol level of 198 mg/dL, has blood pressure of 131 mmHg, parents having heart disease medical record, suffering diabetes Mellitus, has obesity, has high dyslipidemia. It is concluded that the object falls into "potential category" of having heart disease. The classification result that has been done, the exact accuracy was obtained with 25 tested data and got accuracy level in an amount of 80% and 50 tested data sample and got accuracy level in an amount of 78%.