Design of Expert System for Diagnosis of Gonorrhea Disease by using Web-Based Naïve Bayes Method

Teri Ade  Putra; Raja Ayu Mahessya; Pradani Ayu Widya Purnama; Reza Suriadinata

doi:10.47709/cnahpc.v3i2.1026

Authors

Teri Ade Putra Universitas Putra Indonesia “YPTK” Padang
Raja Ayu Mahessya Universitas Putra Indonesia “YPTK” Padang
Pradani Ayu Widya Purnama Universitas Putra Indonesia “YPTK” Padang
Reza Suriadinata Universitas Putra Indonesia “YPTK” Padang

DOI:

https://doi.org/10.47709/cnahpc.v3i2.1026

Keywords:

Expert System, Gonorrhea, Naive Bayes, Web Based, MySQL, PHP

Abstract

Gonorrhea is a sexually transmitted disease caused by the bacterium Neisseria gonorrhea that infects the lining of the bladder, cervix, rectum, throat, and the whites of the eyes. This disease is spread through the bloodstream to other parts of the body, especially the skin and joints and is generally transmitted through sexual contact. Gonorrhea not only affects adult men and women, but babies and even newborns can get gonorrhea from their mothers. An expert system is a system that seeks to adopt human knowledge into computers, so that computers can solve problems like an expert. With this expert system, the public can obtain information or can solve the problems they face which can only be obtained with the help of experts in their fields. This study explains how the expert system diagnoses Gonorrhea using the Naïve Bayes method. By using the Naïve Bayes method, it can predict future probability values based on previous experiences experienced by people with gonorrhea, Document classification can be personalized, tailored to the needs of each person. By using this expert system application, it can provide information and make it easier for the public to be more familiar with Gonorrhea and can handle problems based on the expertise of doctors who are experts in their fields. This expert system can provide solutions and prevention of gonorrhea disease with the diagnosis process carried out efficiently and save time in helping the community in the prevention that occurs. This web-based expert system application is built with the PHP programming language and MySQL data storage.

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