Implementasi Metode Naive Bayes Pada Media Facebook Untuk Analisis Indikasi Pengidap Virus COVID-19 Varian Omicron di Indonesia dengan Menggunakan Aplikasi Sistem Pakar Berbasis Web - Redo Ramadhan Caniago; Jaka Sutresna (CV. Multi Kreasi Media, 2023)
The Covid-19 virus is a fairly dangerous disease due to various triggering factors and symptoms that appear including runny nose, fever, cough, sore throat and others. The public also ignores the symptoms that occur and does not check with the doctor because they think the disease is a disgrace so that many people with Covid-19 are in a worse condition and cause death. Researchers also have an idea to implement an Expert System Application using the Web-Based Naïve Bayes Method on Facebook Media for the Analysis of Indications of the Omicron variant of the Covid-19 Virus in Indonesia with the aim of making it easier for people to diagnose diseases and recognize the symptoms of covid-19. This expert system uses the nave Bayes method which is a method for predicting the chance of the occurrence of covid-19 disease based on a weight that has been determined by an expert. This study uses the waterfall model as a guide for designing an expert system and to facilitate program development on an expert system. The results of this study obtained an expert system for analyzing indications of covid-19 disease with a web-based nave Bayes method that makes it easy for lay people and experts to make it easier to get treatment for early actions when diagnosed with the omicron variant of covid-19 It was concluded that there was a relationship between the level of ignorance and the frequency with which facilities to support facilities and understanding of covid-19 existed, so with the application of the expert system that was made, hopefully it can help the community to simplify and understand about covid-19.