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Implementasi Sistem Pendeteksi Myocardial Ischemia menggunakan Metode Support Vector Machine (SVM) Ezra Maherian; Rizal Maulana; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Myocardial Ischemia is a condition occurs when the blood flow to the heart is reduced, making the heart muscle lack of oxygen supply. The reduced blood flow occurs due to blockage inside the coronary arteries which could be the build-up of cholesterol or the clotting of the blood. The blockage could build-up even more from time to time, blocking the blood flow entirely and making the person with the condition more prone to a heart attack. Commonly, diagnosing Myocardial Ischemia is done by medical professionals at the hospital. AD8232 sensor kit and Arduino Uno Microcontroller are used to detect Myocardial Ischemia. The detection of heart condition is based on the slope of ST-segment and the peak of T wave that will be classified by Support Vector Machine classifier into either Myocardial Ischemia or Normal class. As many as 40 data were used to train the system and as many as 20 data were used to test the system. Sensor accuracy test shows sensor's accuracy of 95.56%. Test of SVM computation time gives a result of 3912.30 ms for average training time and 0.061 ms for average testing time. The accuracy of SVM classification tested on 20 data gives an accuracy rate of 85%.