Implementation of The Naïve Bayes Algorithm For Diagnosing Lung Disesase In An Expert System Concept

Hafiyyan, Azka
Seniwati, Erni
Haryoko, H

IJISTECH
Vol 7, No 1 (2023): The June edition

Web-based lung disease diagnosis expert system is an application designedto help diagnose lung disease quickly and accurately. This system uses the Naïve Bayes classification method which is one of the techniques in artificial intelligence. The Naïve Bayes method utilizes probability to classify data based on existing attributes. In the context of a lung disease expert system, these attributes can include symptoms experienced by patients such as cough, shortness of breath, chest pain, and so on. Research results have shown that in the test of accuracy comparing the expert with the lung disease diagnostic system using the naive Bayes method, the accuracy rate reached 86.66%. With the achieved accuracy rate, it can be stated that the system is capable of performing diagnoses effectively and accurately