Sistem Pakar Akurasi dalam Mengidentifikasi Penyakit Gingivitis pada Gigi Manusia dengan Metode Naive Bayes

Abstract

Gingivitis is a condition where the gums become inflamed due to a bacterial infection, causing the gums to swell. Gingivitis if treated too late will trigger more dangerous dental disease. Minimize knowledge about gingivitis and limited time to consult with experts so that people pay less attention to dental and oral health which can indicate gingivitis. The purpose of this study was to determine accuracy in identifying gingivitis disease using the Naive Bayes method, which can help the public to find out information about gingivitis, so a system with experts was built. Expert System is knowledge from experts that is entered into a computer or system that can be used for consultation. The data used in this study were 24 symptom data and 5 types of disease data sourced from interviews with an expert. The experts used in this study were dentists at the Rahmatan Lil Alamin Clinic. The data can be obtained from the results of the medical records of patients who perform examinations with dentists. The data processed in this study is knowledge about the symptoms and types of gingivitis in the teeth obtained from an expert. The result of the test is that the largest value of the total probability is found in the type of gum disease Puberty with a value of 0.000106795855. This research can help the community to conduct consultations easily, find out the symptoms early so that people do not have to go to the hospital with a long distance.