Penerapan Algoritma Naïve Bayes Dalam Diagnosa Penyakit Covid-19

Abstract

Covid-19 is a virus that is so small that you cannot see it with the naked eye, you need the help of a magnifying device such as a microscope and this virus is very dangerous which causes respiratory problems in humans and can even kill humans who have been exposed to the Covid-19 virus or other viruses. this crown. Where in general, the community and medical teams diagnose someone who has been exposed to Covid-19 based on a symptom including: fever, cough, runny nose, shortness of breath, unable to smell and feel on the tongue. But not everyone who suffers from such a disease can be classified as Covid -19 disease. So to make sure someone has Covid-19, an antigen test or PCR test is carried out. Examination data related to Covid-19 from the results of symptoms with the results of antigen or PCR tests has been collected and has not been used to diagnose someone who has symptoms of Covid-19. From the problems that exist, the medical team really needs help in diagnosing Covid-19 disease in patients easily and quickly, namely by using the Naïve Bayes algorithm data mining, where the Naïve Bayes algorithm can produce correct and real data. The results of this study are based on the Naïve Bayes data mining algorithm in the diagnosis of Covid-19, namely Alex is positive for Covid-19 while Imam is negative for Covid-19.