Application of the Naive Bayes Method in Expert Systems for Diagnosing Gingivitis - Fernando, Rendy; Suranti , Dewi; Suryana , Eko (Jurnal Komputer Indonesia, 2022)
The number of program activities at the Beringin Raya Health Center in Bengkulu City is sometimes not proportional to the number of doctors in the puskesmas, so not all patients can have health consultations, especially about gingivitis. Gingivitis is a disease caused by a bacterial infection which causes the gums to swell due to inflammation. Therefore we need an application that can help the process of diagnosing gingivitis based on the symptoms experienced by the patient, so that the initial diagnosis experienced by the patient can be known. The expert system for diagnosing gingivitis at the Beringin Raya Nursing Health Center in Bengkulu City was made using the PHP programming language and MySQL database, which can be accessed online via the https://sistempakargingivitis.my.id/ link. The expert system for diagnosing gingivitis in the treatment of Beringin Raya, Bengkulu City, has implemented the Naive Bayes Method to represent, combine, and propagate uncertainty, which has several intuitive characteristics according to the way of thinking of an expert. The training data used is 11 data which is used as the basis for the probability value of each symptom in the disease to carry out a consultation diagnosis. Based on the consultation with the selected symptoms, namely G1, G2, G3 and G4, the diagnosis of Nonvital Teeth disease (Dead Teeth) was obtained with a bayes value of 0.2045454541875. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consulting results based on the symptoms selected by the user through the stages of the Naive Bayes method