# COMPARATIVE ANALYSIS OF K-NEAREST NEIGHBOR AND SUPPORT VECTOR MACHINE IN CLASSIFICATION OF COVID 19 DISEASE IN MAKASSAR CITY
> Abuspin M.A.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85205263263
Jurnal / Konferensi: Communications in Mathematical Biology and Neuroscience
Tahun terbit: 2024
DOI: https://doi.org/10.28919/cmbn/8774
ISSN: 20522541
Kuartil SJR: Q4
Citations: 0

## Authors
- Abuspin M.A.

## 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.

## Keywords
- k-nearest neighbors algorithm
- Support vector machine
- Coronavirus disease 2019 (COVID-19)
- Pattern recognition (psychology)
- Artificial intelligence
- Disease
- Computer science
- Geography
- Medicine
- Pathology
- Infectious disease (medical specialty)

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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