International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Identification of Cardiovascular Disease Based on Echocardiography and Electrocardiogram Data Using the Decision Tree Classification Approach

  • Tb Ai Munandar (Faculty of Information Technology, Universitas Serang Raya) ;
  • Sumiati (Faculty of Information Technology, Universitas Serang Raya) ;
  • Vidila Rosalina (Faculty of Information Technology, Universitas Serang Raya)
  • Received : 2023.09.05
  • Published : 2023.09.30
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Abstract

For a doctor, diagnosing a patient's heart disease is not easy. It takes the ability and experience with high flying hours to be able to accurately diagnose the type of patient's heart disease based on the existing factors in the patient. Several studies have been carried out to develop tools to identify types of heart disease in patients. However, most only focus on the results of patient answers and lab results, the rest use only echocardiography data or electrocardiogram results. This research was conducted to test how accurate the results of the classification of heart disease by using two medical data, namely echocardiography and electrocardiogram. Three treatments were applied to the two medical data and analyzed using the decision tree approach. The first treatment was to build a classification model for types of heart disease based on echocardiography and electrocardiogram data, the second treatment only used echocardiography data and the third treatment only used electrocardiogram data. The results showed that the classification of types of heart disease in the first treatment had a higher level of accuracy than the second and third treatments. The accuracy level for the first, second and third treatment were 78.95%, 73.69% and 50%, respectively. This shows that in order to diagnose the type of patient's heart disease, it is advisable to look at the records of both the patient's medical data (echocardiography and electrocardiogram) to get an accurate level of diagnosis results that can be accounted for.

Keywords

Acknowledgement

Thank you to the Ministry of Research, Technology and Higher Education of Republic of Indonesia for funding this basic research scheme through the Directorate General of Research and Development Strengthening of RISTEK DIKTI.

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