Abstract
Heart disease is a disease that is very dangerous for human survival, the World Health Organization (WHO) states in 2016 an estimated 17.9 million people died from cardiovascular disease, of these deaths 85% were caused by heart attacks and strokes. More than three-quarters of deaths from cardiovascular disease occur in low-income countries (WHO, 2017). Therefore, heart disease must be treated early when symptoms appear. Advances in Artificial Intelligence technology, one of which is an expert system, can overcome this problem by designing a web-based computer system that uses databases and programming languages such as PHP-MySQL so that it can help heart patients to diagnose the disease. Therefore, the author has the aim of this study is to build a web-based expert system for diagnosing heart disease. This expert system application uses the Nearest Neighbor Retrieval method in order to represent the knowledge of cardiologists and can be useful for the community. This system can diagnose 27 symptoms or conditions related to heart disease, so that the diagnosis of these symptoms will produce output in the form of the probability of possible disease according to the correlation of the symptoms entered. This system is effective enough to be used as an alternative solution for the community in diagnosing heart disease, because this system has been tested by experts and produces an accuracy rate of 90.00%.
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