Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia

The COVID-19 pandemic is the first and foremost health crisis in the world.  Coronavirus is a collection of viruses from the subfamily Orthocronavirinae in the Coronaviridae family and the order of Nidovirales.  This group of viruses that can cause disease in birds and mammals, including humans.  In...

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Main Authors: Alvina Felicia Watratan, Arwini Puspita. B, Dikwan Moeis
Format: Article
Language:Indonesian
Published: Indonesian Society of Applied Science (ISAS) 2020-07-01
Series:Journal of Applied Computer Science and Technology
Subjects:
Online Access:https://journal.isas.or.id/index.php/JACOST/article/view/9
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author Alvina Felicia Watratan
Arwini Puspita. B
Dikwan Moeis
author_facet Alvina Felicia Watratan
Arwini Puspita. B
Dikwan Moeis
author_sort Alvina Felicia Watratan
collection DOAJ
description The COVID-19 pandemic is the first and foremost health crisis in the world.  Coronavirus is a collection of viruses from the subfamily Orthocronavirinae in the Coronaviridae family and the order of Nidovirales.  This group of viruses that can cause disease in birds and mammals, including humans.  In humans, coronaviruses cause generally mild respiratory infections, such as colds, although some forms of disease such as;  SARS, MERS, and COVID-19 are more deadly. Anticipating and reducing the number of corona virus sufferers in Indonesia has been carried out in all regions.  Among them by providing policies to limit activities out of the house, school activities laid off, work from home (work from home), even worship activities were laid off.  This has become a government policy based on considerations that have been analyzed to the maximum, of course. Therefore this research was carried out as an anticipation step towards the Covid-19 pandemic by predicting the spread of Covid-19, especially in Indonesia. The research method applied in this research is problem analysis and literature study, collecting data and implementation.  The application of the naive bayes method is expected to be able to predict the spread rate of COVID-19 in Indonesia. The results of the Naive Bayes method classification show that 16 data from 33 data were tested in Covid-19 cases per province with an accuracy of 48.4848%, where of the 33 data tested in the Covid-19 case per province tested there were 16 data that were successfully classified correctly.
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spelling doaj.art-f5ba31719e744ff8824e9f126fb93e0d2022-12-21T21:59:18ZindIndonesian Society of Applied Science (ISAS)Journal of Applied Computer Science and Technology2723-14532020-07-011171410.52158/jacost.v1i1.99Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di IndonesiaAlvina Felicia Watratan0Arwini Puspita. B1Dikwan Moeis2STMIK Profesional MakassarSTMIK Profesional MakasarSTMIK Profesional MakasarThe COVID-19 pandemic is the first and foremost health crisis in the world.  Coronavirus is a collection of viruses from the subfamily Orthocronavirinae in the Coronaviridae family and the order of Nidovirales.  This group of viruses that can cause disease in birds and mammals, including humans.  In humans, coronaviruses cause generally mild respiratory infections, such as colds, although some forms of disease such as;  SARS, MERS, and COVID-19 are more deadly. Anticipating and reducing the number of corona virus sufferers in Indonesia has been carried out in all regions.  Among them by providing policies to limit activities out of the house, school activities laid off, work from home (work from home), even worship activities were laid off.  This has become a government policy based on considerations that have been analyzed to the maximum, of course. Therefore this research was carried out as an anticipation step towards the Covid-19 pandemic by predicting the spread of Covid-19, especially in Indonesia. The research method applied in this research is problem analysis and literature study, collecting data and implementation.  The application of the naive bayes method is expected to be able to predict the spread rate of COVID-19 in Indonesia. The results of the Naive Bayes method classification show that 16 data from 33 data were tested in Covid-19 cases per province with an accuracy of 48.4848%, where of the 33 data tested in the Covid-19 case per province tested there were 16 data that were successfully classified correctly.https://journal.isas.or.id/index.php/JACOST/article/view/9covid-19naïve bayesaplikasi weka
spellingShingle Alvina Felicia Watratan
Arwini Puspita. B
Dikwan Moeis
Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
Journal of Applied Computer Science and Technology
covid-19
naïve bayes
aplikasi weka
title Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
title_full Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
title_fullStr Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
title_full_unstemmed Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
title_short Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia
title_sort implementasi algoritma naive bayes untuk memprediksi tingkat penyebaran covid 19 di indonesia
topic covid-19
naïve bayes
aplikasi weka
url https://journal.isas.or.id/index.php/JACOST/article/view/9
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