Identifying Drug Selection for Patients Using the Desicion Tree Method

Abstract

Hypertension also known as high blood pressure, is a medical condition in which arterial blood pressure is consistently lower than normal. Hypercholesterolemia, also known as high cholesterol, is a condition where the amount of cholesterol in the blood is too high. These two conditions often occur together and require appropriate drug management to reduce cardiovascular risk. This study aims to identify variables that influence drug use by patients with high blood pressure and cholesterol using the Desicion Tree classification method. The Desicion Tree classification method was used in the study to understand whether treatment might be appropriate for patients with the same condition in the future. The dataset consists of: Age, Gender, Blood Pressure, and cholesterol, sodium-potassium, and medication. The use of the Desicion Tree algorithm with RapidMiner shows an accuracy of 99%, which proves the effectiveness of the method in providing assistance in making higher decisions regarding determining drugs for patients. It is hoped that this research can help doctors in making decisions regarding drug selection for patients.