PERBANDINGAN MODEL DECISION TREE, NAIVE BAYESDAN RANDOM FOREST UNTUK PREDIKSI KLASIFIKASIPENYAKIT JANTUNG - Deo Haganta Depari (2022)
The heart is a muscular organ cavity that pumps blood through blood vessels with rhythmic contractions that keep repeating itself is one of the human organs that plays a role in the circulatory system. The heart as one of the most important organs in the body has a risk of death if there are abnormalities that occur in the heart. Some heart problems are divided into two, namely heart disease and heart attack. WHO based on data states that there are as many as 7.3 million people in the world who died due to heart disease. This study uses a data collection of heart disease patients "Personal Key Indicators of Heart Disease" and applies the Decision Tree, Naive Bayes and Random Forest classification algorithms. The purpose of this research is how to process and analyze data, how to apply the Decision Tree, Naive Bayes and Random Forest methods to the classification of heart disease, then how are the results of the accuracy of the methods used, how are the results of the comparison between Decision Tree, Naive Bayes and Random Forests used and what method is the best of classification of heart disease. The result of this research is an evaluation of the performance of the Decision Tree, Naive Bayes and Random Forest classification methods. Where the accuracy value of the Decision Tree method is 0.71%, Naive Bayes is 0.72% and Random Forest is 0.75%.