文章基本信息

标题：Machine Learning Algorithms for Predicting the Spread of Covid‒19 in Indonesia
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作者：Syafri Arlis ; Sarjon Defit
期刊名称：TEM Journal
印刷版ISSN：2217-8309
电子版ISSN：2217-8333
出版年度：2021
卷号：10
期号：2
页码：970-974
DOI：10.18421/TEM102-61
语种：English
出版社：UIKTEN
摘要：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%.