Visualization of Prediction of The Spread of Covid-19 in Indonesia using Cellular Automata

The first case of COVID 19 was detected in Indonesia in early March 2020. One way to assist the government in making decisions to deal with COVID-19 is to create a map of the distribution of COVID-19 patients based on which can only be accessed by people who have an interest through the website. The data used in this study is the period, location, total cases. After getting the data, the data is then processed to get weekly rules. After getting the weekly rules, the data is entered into the calculation of the Moore scheme to get the prediction results for the next week. Then the prediction results are poured in the form of a map. The prediction process using CA neighbors is carried out using Moore's formula, a formula that applies the adjacent neighbors of 8 neighbors. The accuracy level of Cellular Automata with Moore's neighbors reaches 431.1466353% using MAPE. The error value in the Cellular Automata method is quite high due to several factors that make the prediction results with the original data results different, but this method can be used to research cases of covid 19

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Publication Details

Journal
International Journal of Computer and Information Technology(2279-0764)
Published
2024-10-18
DOI
https://doi.org/10.24203/htdzgq15
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Visualization of Prediction of The Spread of Covid-19 in Indonesia using Cellular Automata

Dian Pratiwi, Safira Aurellia Azzahra, Syandra Sari
International Journal of Computer and Information Technology(2279-0764)
Data Mining and Machine Learning Applications
article

Visualization of Prediction of The Spread of Covid-19 in Indonesia using Cellular Automata

Dian Pratiwi, Safira Aurellia Azzahra, Syandra Sari
article en

Abstract

The first case of COVID 19 was detected in Indonesia in early March 2020. One way to assist the government in making decisions to deal with COVID-19 is to create a map of the distribution of COVID-19 patients based on which can only be accessed by people who have an interest through the website. The data used in this study is the period, location, total cases. After getting the data, the data is then processed to get weekly rules. After getting the weekly rules, the data is entered into the calculation of the Moore scheme to get the prediction results for the next week. Then the prediction results are poured in the form of a map. The prediction process using CA neighbors is carried out using Moore's formula, a formula that applies the adjacent neighbors of 8 neighbors. The accuracy level of Cellular Automata with Moore's neighbors reaches 431.1466353% using MAPE. The error value in the Cellular Automata method is quite high due to several factors that make the prediction results with the original data results different, but this method can be used to research cases of covid 19

International Journal of Computer and Information Technology(2279-0764)Vol. 13(3)
Universitas Trisakti (ID)
Openalex Percentile: Top 52%
Data Mining and Machine Learning Applications
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Visualization of Prediction of The Spread of Covid-19 in Indonesia using Cellular Automata — Dian Pratiwi, Safira Aurellia Azzahra, et al. · International Journal of Computer and Information Technology(2279-0764) (2024) | TGRS Research Map | TGRS