COVID-19 Outbreak Data Analysis and Prediction Modeling Using Data Mining Technique

  • Tajebe Tsega Mengistie NITM, Bijni Complex, Laitumkhrah, Shillong, Meghalaya 793003, India
Keywords: Prediction modeling, Analysis and Visualization, Time Series, Fbprophet, COVID-19

Abstract

Nowadays, sustainable development is considered a key concept and solution in creating a promising and prosperous future for human societies. Nevertheless, there are some predicted and unpredicted problems that epidemic diseases are real and complex problems. Hence, in this research work, a serious challenge in the sustainable development process was investigated using the classification of confirmed cases of COVID-19 (new version of Coronavirus) as one of the epidemic diseases. Hence, the data mining predictive modeling method of data handling and predictive or forecasting the spread of COVID-19 virus. This research work mainly works on predicting or forecasting by using fbprophet. Prophet it is a python library package used for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonally, plus holiday’s effect. It works best with time series that have a strong seasonal effect and several seasons of historical data. The model helps to interpret patterns of public sentiment on disseminating related health information and assess the political and economic influence of the spread of the virus.

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Published
2020-05-14
How to Cite
Mengistie, T. T. (2020). COVID-19 Outbreak Data Analysis and Prediction Modeling Using Data Mining Technique. International Journal of Computer (IJC), 38(1), 37-60. Retrieved from https://www.ijcjournal.org/index.php/InternationalJournalOfComputer/article/view/1659
Section
Articles