COMPARATIVE ANALYSIS OF K-NEAREST NEIGHBOR AND SUPPORT VECTOR MACHINE IN CLASSIFICATION OF COVID 19 DISEASE IN MAKASSAR CITY

Abstract

Coronavirus disease 2019 or better known as COVID-19 is an outbreak that was initially detected in the city of Wuhan, China in December 2019. Before it was called COVID-19, WHO or the World Health Organization gave this new virus a temporary name as 2019 Novel Coronavirus (2019). nCoV). And on April 21 2020 WHO officially called the 2019-nCoV virus COVID-19. There are 4 factors that influence COVID 19 patients and these factors will be considered. To analyze the impact of the factors, the K-Nearest Neighbor (kNN) and Support Vector Machine (SVM) algorithms use JASP. The aim of this research is determine the comparison of classification accuracy levels K-Nearest Neighbor and Support Vector Machine towards Covid 19 patients. The results show that SVM achieved a higher level of accuracy, namely 98.43% compared to the kNN method which produced an accuracy of 98.40%, when applied to COVID 19 patient data in Makassar city.

Access to Document

Other files and links

• Link to publication in Scopus
• Open Access Version Available

Fingerprint