Decision Support System for Heart Disease Diagnosing Using K-NN Algorithm

Tito Yuwono (Islamic University of Indonesia)
Noor Akhmad Setiawan (Gadjah Mada University)
Adi Nugroho (Gadjah Mada University)
Anugrah Galang Persada (Gadjah Mada University)
Ipin Prasojo (Islamic University of Indonesia)
Sri Kusuma Dewi (Islamic University of Indonesia)
Ridho Rahmadi (Islamic University of Indonesia)

Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 2: EECSI 2015

Heart disease is a notoriously dangerous disease whichpossibly causing the death. An electrocardiogram (ECG) is used fora diagnosis of the disease. It is often, however, a fault diagnosis by adoctor misleads to inappropriate treatment, which increases a riskof death. This present work implements k-nearest neighbor (K-NN)on ECG data to get a better interpretation which expected to help adecision making in the diagnosis. For experiment, we use an ECGdata from MIT BIH and zoom in on classification of three classes;normal, myocardial infarction and others. We use a single decisionthreshold to evaluate the validity of the experiment. The resultshows an accuracy up to 87% with a value of K = 4