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All Journal PELS (Procedia of Engineering and Life Science)
Fandy Rachmatulloh
Universitas Muhammadiyah Sidoarjo, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Expert System for Diagnosing Liver Disease Using Web-Based Bayes Theorem Method Metode Fandy Rachmatulloh; Ade Eviyanti
Procedia of Engineering and Life Science Vol 1 No 2 (2021): Proceedings of the 2nd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.359 KB) | DOI: 10.21070/pels.v1i2.970

Abstract

Many people still do not know the risks, prevention, and treatment solutions related to liver disease. Therefore, many Indonesian people are affected by liver diseases such as hepatitis and other liver diseases because they are not aware of the symptoms they are experiencing. Therefore, this expert system is designed to help diagnose the symptoms experienced by people or patients who have liver disease. With this expert system, it can help overcome delays in handling so that it is not severe later. This expert system is created using the Bayes theorem method where in each symptom there is a probability or possibility which then gets the final result in the form of how big the event occurred. This expert system diagnoses the symptoms selected by the patient. After that, get the value of the possibility of a disease suffered by the patient. The results of this study are to produce an expert system for diagnosing liver disease using the website-based Bayes theorem method. This system can help diagnose a patient’s symptoms quickly and is used anywhere.
Co-Authors Ade Eviyanti