Open AccessKOMPARASI ALGORITMA NEURAL NETWORK DAN NAÏVE BAYES UNTUK MEMPREDIKSI PENYAKIT JANTUNG
Author(s) -
Hendri Mahmud Nawawi,
Jajang Jaya Purnama,
Agung Baitul Hikmah
Publication year - 2019
Publication title -
pilar nusa mandiri/pilar nusa mandiri
Language(s) - English
Resource type - Journals
eISSN - 2527-6514
pISSN - 1978-1946
DOI - 10.33480/pilar.v15i2.669
Subject(s) - heart disease , disease , bayes' theorem , medicine , computer science , artificial intelligence , bayesian probability
Heart disease is one of the types of deadly diseases whose treatment must be dealt with as soon as possible because it can occur suddenly to the sufferer. Factors of heart disease that are recognized based on the condition of the body of a sufferer need to be known from an early age so that the risk of possible instant attacks can be minimized or can be overcome in various ways such as a healthy lifestyle and regular exercise that can regulate heart health in the body. By looking at the condition of a person's body based on sex, blood pressure, age, whether or not a smoker and some indicators that become a person's characteristics of heart disease are described in a study using the Neural Network and Naïve Bayes algorithm with the aim of comparing the level of accuracy to attributes influential to predict heart disease, so the results of this study can be used as a reference to predict whether a person has heart disease or not.