Perbandingan Random Forest, Decision Tree, Gradient Boosting, Logistic Regression untuk Klasifikasi Penyakit Jantung
Abstract
Heart disease is a condition characterized by disorders affecting the heart. These heart disorders include infections, abnormalities in heart valves, blockages in the heart's blood vessels, irregular heartbeats, and so on. According to a report by the World Health Organization (WHO) in 2019, approximately 17.9 million people died from cardiovascular diseases, with 85% of them attributed to heart attacks and strokes. The shortage of doctors and specialists can lead to negligence and the overlooking of patients' symptoms, which can result in disabilities or even death for the patients. Therefore, the need for an expert system arises, which can be utilized as a tool to classify or detect heart diseases based on patients' medical records. Based on the results of the conducted research, random forest is a fairly effective algorithm for classifying heart diseases, with a recall value of 80.6% and ROC AUC of 76.3%.
Keywords: Classification, Random Forest, Decision Tree, Gradient Boosting, Logistic Regression, Heart Disease
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