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Ridho Rahmadi
Islamic University of Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Decision Support System for Heart Disease Diagnosing Using K-NN Algorithm Yuwono, Tito; Setiawan, Noor Akhmad; Nugroho, Hanung Adi; Persada, Anugrah Galang; Prasojo, Ipin; Dewi, Sri Kusuma; Rahmadi, Ridho
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.2.544

Abstract

Heart disease is a notoriously dangerous disease which possibly causing the death. An electrocardiogram (ECG) is used for a diagnosis of the disease. It is often, however, a fault diagnosis by a doctor misleads to inappropriate treatment, which increases a risk of death. This present work implements k-nearest neighbor (K-NN) on ECG data to get a better interpretation which expected to help a decision making in the diagnosis. For experiment, we use an ECG data from MIT BIH and zoom in on classification of three classes; normal, myocardial infarction and others. We use a single decision threshold to evaluate the validity of the experiment. The result shows an accuracy up to 87% with a value of K = 4.
Co-Authors Anugrah Galang Persada, Anugrah Galang Hanung Adi Nugroho Ipin Prasojo, Ipin Noor Akhmad Setiawan Sri Kusuma Dewi, Sri Kusuma Tito Yuwono, Tito