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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Qurrata Ayuni
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Aritmia Dari Hasil Elektrokardiogram Menggunakan Metode Support Vector Machine Qurrata Ayuni; Randy Cahya Wihandika; Novanto Yudistira
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Arrhythmia (heart rhythm disorder) is a disorder of the cardiac elektrophysology caused by disruption of the conduction system as well as impaired formation and delivery of electrical impulses. Some factors that influence arrhythmia include age, blood pressure, height and weight. This arrhythmia can be recognized by using a cardiac record or electrocardiogram (ECG). Numerical data generated by ECG has many features that are not easily processed manually. Computer assistance with certain machine learning techniques can be used to automatically recognize diseases. One method of machine learning is support vector machine (SVM). In this study, a system was designed to classify arrhythmias using support vector machine (SVM) methods. The most optimal accuracy value or accuracy that has the highest value indicates that the system is in accordance with expectations, so that the support vector machine method is able to measure the accuracy of the classification of arrhythmias based on electrocardiogram results with RBF kernel function of 92%.
Co-Authors Novanto Yudistira Randy Cahya Wihandika