Rapid Test Stock Prediction of Priority Health Facilities Using Naïve Bayes Algorithm
Hartatik Hartatik, Rudi Hartono, Nurul Firdaus, Muhammad Yusuf, Eko Harry Pratisto, Berliana Kusuma Riasti · 2022
Handling the rapid spread of the Coronavirus that is currently engulfing the world is critical to suppress the development of the Coronavirus. one of them is rapid test distribution management. The rapid Test is an initial screening method for detecting antibodies, namely IgM and IgG, which are produced by the body to fight the Coronavirus / Antibodies that will be formed by the body when there is exposure to the Coronavirus. So, a rapid test is a screening tool, not an examination, to diagnose Coronavirus infection or COVID-19. For this reason, in current conditions, it is necessary to have a good arrangement in terms of distribution and regulation of the rapid test stock. Distributing the Corona (Covid 19) rapid Test prioritizes health facilities in areas that are the epicenter of the Corona spread. For this reason, this study provides a Rapid Test Using the Naïve Bayes Data Mining Algorithm. In this study, data obtained from data collection were then classified based on the framework used to conduct further analysis using the Simple Additive Weighting and Naive Bayes algorithm. This research results to determine the distribution of the rapid test tool based on stock data to be used for forecasting the distribution model.