COVID-19 Spread Pattern Using Support Vector Regression

PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)

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Field Value
 
Title COVID-19 Spread Pattern Using Support Vector Regression
 
Creator Herlawati, Herlawati
 
Description Pandemics are rare and happen in about 100 years period. Current pandemic, COVID-19, occurs in the industrial 4.0 era where there is a rapid development computation. Yet, the scientists in every country face difficulty in predicting the growth simulation of this pandemic. The paper tries to use a soft computing algorithm to predict the pattern of the COVID-19 pandemic in Indonesia. Support Vector Regression was used in Google Interactive Notebook with some kernels for comparison, i.e. radial basis function, linear and polynomial. The testing results showed that radial basis function outperformed other kernels as a regressor with some parameters should follows the real condition, i.e. gamma, c, and epsilon.
 
Publisher LPPM Universitas Islam 45 Bekasi
 
Date 2020-03-28
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://jurnal.unismabekasi.ac.id/index.php/piksel/article/view/2024
10.33558/piksel.v8i1.2024
 
Source PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic; Vol 8 No 1 (2020): Maret 2020; 67 - 74
2620-3553
2303-3304
10.33558/piksel.v8i1
 
Language eng
 
Relation http://jurnal.unismabekasi.ac.id/index.php/piksel/article/view/2024/1650
 
Rights Copyright (c) 2020 PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
 

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