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Muhammad Misdram
Program Studi Informatika, Universitas Merdeka Pasuruan
Computer Science & IT

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KLASIFIKASI DATA SET VIRUS CORONA MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Muhammad Misdram; Fahmi Syarifuddin; Anang Aris Widodo
SPIRIT Vol 12, No 2 (2020): SPIRIT
Publisher : STMIK YADIKA BANGIL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53567/spirit.v12i2.184

Abstract

Abstract: At the beginning of 2020 the world of health was shocked by the discovery of a new virus that was known to have originated from this virus in Wuhan, China. Almost the whole world has experienced this virus pandemic. Then on February 11, 2020, the World Health Organization named the new virus Severa acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the name of the disease as Coronavirus Disease 2019 (COVID-19) (WHO, 2020). At first, the transmission of this virus could not be determined whether it was between animal-human or human-human. Meanwhile, the number of cases continues to increase over time. At that time, there were 15 medics infected by one of the patients. It was finally confirmed that the transmission of pneumonia can be transmitted from human to human. Until now, the handling of Covid-19 patients is still continuing. This is because the number of patients continues to grow every day. For this reason, an application is needed that can monitor the cure rate for Covid-19 patients. This system is built using the Naïve Bayes Classification (NBC) method. The NBC method is a method used for classification and can predict future opportunities based on past experiences. The test results show that using the Nive Bayes Method has a fairly good accuracy, namely 84%. Keywords : Covid-19, classification, Naïve Bayes Classifier
Co-Authors Anang Aris Widodo, Anang Aris Fahmi Syarifuddin