Predicting the Number of People Exposed to Covid 19 with the Newton Gregory Maju Polynomial Interpolation Method

F. Anthon Pangruruk; Simon P.  Barus

doi:10.55927/fjst.v1i8.2185

Authors

F. Anthon Pangruruk Universitas Matana
Simon P. Barus Universitas Matana

DOI:

https://doi.org/10.55927/fjst.v1i8.2185

Keywords:

Prediction, Covid-19, Interpolation, Newton Gregory Maju

Abstract

Since March 2020 until now the Corona Virus (Covid-19) is still running rampant and even new variants have appeared. The increase in people exposed to this virus can cripple the community's economy. The government must be able to anticipate the increasingly high spread of Covid-19. Therefore, a prediction model is needed for the number of people exposed to Covid-19 so that the government can anticipate it as a preventive measure. Research that has been carried out since early 2021 using the Monte Karlo, Arima, K-Nearest Neighbors methods, Time Series Analysis, Winter and Artificial Neural Networks. Furthermore, the researchers predicted the number of people exposed to Covid-19 using the Newton Gregory Maju interpolation method. The prediction results for the DKI Jakarta area in March 2022 are based on historical data for January - February 2022 with the smallest error of 2.17%, the highest error of 46.28% and the average error of 17.27%.

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