Expert system for heart disease based on electrocardiogram data using certainty factor with multiple rule

Sumiati Sumiati, Hoga Saragih, Titik Abdul Rahman, Agung Triayudi


Limited public health services in remote areas, where the lack of transportation infrastructure, facilities, communication facilities and minimal medical personnel, especially for areas with underdeveloped, foremost, and regular (3T) status. The limitation of medical personnel is one of the factors for the high mortality rate of heart disease. On the other hand, the development of information technology, especially in the field of computing, is very fast in the era of the industrial revolution 4.0, but not yet used optimally, especially in the health sector. This study aims to develop a system or software that can replace a doctor for the process of identifying heart defects based on an expert system. Expert system developed with the certainty factor with multiple rule approach. System testing is carried out from the results of the system validity with experts, so that the system test results produce a certainty factor value for a normal heart of 0.95 and an accuracy level of 95%, while the certainty factor (CF) value for an abnormal heart is 0.99 and produces an accuracy rate of 99%.


Accuracy; Certainty factor; Expert systems; Heart disease; Multiple rule

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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