Klasifikasi Tingkat Risiko Hipertensi Menggunakan Algoritma Support Vector Machine (SVM)

Abstract

Blood pressure that is higher than normal is known as hypertension. So sufferers feel sick and even lead to death. For normal blood pressure measurements, it is 120/80 mmHg. Hypertension is a silent killer. Lack of knowledge among health professionals and lay people regarding this disease is the main cause of uncontrolled high blood pressure. There are still many people who are not aware of the hypertension disease that affects them. It is possible that the hypertension he is experiencing is acute. High blood pressure cannot be cured, but prevention and control can be done quickly. The number of high blood pressure problems continues to increase in Indonesia. Therefore, an early classification system for types of hypertension is needed based on the history of the disease. By using machine learning technology to extract new knowledge from data to find patterns that are valid, useful, and easy to learn. Therefore, a method was developed to classify human blood pressure values into 4 classes, namely prehypertension, normal, stage 1 hypertension and stage 2 hypertension. The method developed is the Support Vector algorithm which processes a dataset containing 9 features. Based on testing the Support Vector Machine model with Radial Basis Function kernels with 99% Accuracy.