SISTEM KLASIFIKASI DETAK JANTUNG BERDASARKAN ARTIFICIAL NEURAL NETWORK (ANN) DAN PENGURANGAN DIMENSI

PALEDYA, SICILIA and Nurmaini, Siti (2019) SISTEM KLASIFIKASI DETAK JANTUNG BERDASARKAN ARTIFICIAL NEURAL NETWORK (ANN) DAN PENGURANGAN DIMENSI. Undergraduate thesis, Sriwijaya University.

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Abstract

Arrhythmia is one of heart disease characterized by irregular electrical activity or an abnormal heartbeat. Classifying abnormal heartbeats which are symptoms of arrhythmia can be seen from the medical record in the form of an electrocardiogram (ECG). ECG signal records the activity of the heartbeat. The classification of arrhythmia is divided into 6 classes, namely Paced Beat, Atrial Premature, Left Bundle Branch Block Beat, Normal, Right Bundle Branch Block Beat, and Premature Ventricular Contraction. In this study, the classification method used an Artificial Neural Network (ANN) Backpropagation. The result of an ANN Backpropagation method shows an accuracy, F1-score, precision, sensitivity specificity is 99.65%, 99.27%, 96.83%, 97.74%, 99.67%, respectively. This study shows the ANN Backpropagation method can classify heartbeats from arrhythmia through ECG signals.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Arrythmia, Elektrokardiogram (EKG), Klasifikasi, Artificial Neural Network, Backpropagation.
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Q Science > Q Science (General) > Q350-390 Information theory
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Users 1952 not found.
Date Deposited: 19 Sep 2019 08:43
Last Modified: 07 Nov 2019 02:51
URI: http://repository.unsri.ac.id/id/eprint/8138

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