Open AccessExpert System for Diagnosing Liver Disease Using Web-Based Bayes Theorem Method Metode
Author(s) -
Fandy Rachmatulloh,
Ade Eviyanti
Publication year - 2021
Publication title -
procedia of engineering and life science
Language(s) - English
Resource type - Journals
ISSN - 2807-2243
DOI - 10.21070/pels.v1i2.970
Subject(s) - bayes' theorem , expert system , medical diagnosis , disease , liver disease , medicine , hepatitis , indonesian , computer science , artificial intelligence , machine learning , pathology , bayesian probability , gastroenterology , linguistics , philosophy
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.