The Naive Bayes Algorithm in Predicting the Spread of the Omicron
Variant of Covid-19 in Indonesia: Implementation and Analysis
Dublin Core
Title
The Naive Bayes Algorithm in Predicting the Spread of the Omicron
Variant of Covid-19 in Indonesia: Implementation and Analysis
Variant of Covid-19 in Indonesia: Implementation and Analysis
Subject
Covid-19; Naive Bayes; Machine Learning; Data Mining
Description
Indonesia was struck by an epidemic of the corona virus in the start of March 2020, according to official reports (covid).
Indonesia continues to see a rise in the number of cases of covid-19 spreading on a daily basis. The general people are urged to
engage in social distancing in order to disrupt the development of COVID-19, which has spread across Indonesia's numerous
areas. For this reason, this research was undertaken as a preemptive step against the Covid-19 pandemic by estimating the extent
of the Omicron variety of Covid-19's spread around the world, with a particular emphasis on Indonesia. The research
methodologies employed in this study were problem analysis and literature review, as well as data gathering and execution. The
Naive Bayes technique is thought to be capable of estimating the degree of COVID-19 dissemination in Indonesia. The results of
the Naive Bayes method classification study revealed that 16 data from 33 data tested for Covid-19 cases per province were
correctly classified with an accuracy of 46.4252 percent, while 16 data from 33 data tested for Covid-19 cases per province were
misclassified with an accuracy of 46.4252 percent.
Indonesia continues to see a rise in the number of cases of covid-19 spreading on a daily basis. The general people are urged to
engage in social distancing in order to disrupt the development of COVID-19, which has spread across Indonesia's numerous
areas. For this reason, this research was undertaken as a preemptive step against the Covid-19 pandemic by estimating the extent
of the Omicron variety of Covid-19's spread around the world, with a particular emphasis on Indonesia. The research
methodologies employed in this study were problem analysis and literature review, as well as data gathering and execution. The
Naive Bayes technique is thought to be capable of estimating the degree of COVID-19 dissemination in Indonesia. The results of
the Naive Bayes method classification study revealed that 16 data from 33 data tested for Covid-19 cases per province were
correctly classified with an accuracy of 46.4252 percent, while 16 data from 33 data tested for Covid-19 cases per province were
misclassified with an accuracy of 46.4252 percent.
Creator
Jeffri Prayitno Bangkit Saputra 1,*, Racidon P. Bernarte
Date
2022
Contributor
PERI IRAWAN
Format
PDF
Language
ENGLISH
Type
TEXT
Files
Collection
Citation
Jeffri Prayitno Bangkit Saputra 1,*, Racidon P. Bernarte, “The Naive Bayes Algorithm in Predicting the Spread of the Omicron
Variant of Covid-19 in Indonesia: Implementation and Analysis,” Repository Horizon University Indonesia, accessed June 21, 2025, https://repository.horizon.ac.id/items/show/9296.
Variant of Covid-19 in Indonesia: Implementation and Analysis,” Repository Horizon University Indonesia, accessed June 21, 2025, https://repository.horizon.ac.id/items/show/9296.