Machine Learning Algorithms for Predicting the Spread of Covid‒19 in Indonesia

Arlis, Syafri and Defit, Sarjon (2021) Machine Learning Algorithms for Predicting the Spread of Covid‒19 in Indonesia. TEM Journal, 10 (2). pp. 970-974. ISSN 2217-8309

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Abstract

Coronavirus 2019 or Covid-19 is a major problem for health, and it is a global pandemic that has to be controlled. Covid-19 spread so fast to 196 countries, including Indonesia. The government has to study the pattern and predict its spread in order to make policies that will be implemented to tackle the spread of some of the existing data. Therefore this research was conducted as a precautionary measure against the Covid-19 pandemic by predicting the rate of spread of Covid-19. The application of the machine learning method by combining the k-means clustering algorithm in determining the cluster, k-nearest neighbor for prediction and Iterative Dichotomiser (ID3) for mapping patterns is expected to be able to predict the level of spread of Covid-19 in Indonesia with an accuracy rate of 90%. Keywords – machine learning, k-means, k-nearest neighbor, Iterative Dichotomiser

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