Covid-19 Patient Mortality Risk Classification Using Bayesian Binary Logistic Regression

At the end of 2019 world was shocked by a new disease caused SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). The is called Covid-19 (Coronavirus Disease). mortality rate due to increasing every day. In Indonesia as April 2021, confirmed patients who died reached 42,530 patients, seeing high so it needs be studied further that risk death these can minimized. This research utilizing binary logistic regression with Bayesian method parameter estimation. this study, predictor variables used were in form categories each category assumed have same patients. results study indicate number comorbids has significant effect on more suffered patient, higher patient. accuracy classifying data 84.68%.