Comparison of Prediction of the Number of People Exposed to Covid 19 Using the Lagrange Interpolation Method with the Newton Gregory Maju Polynomial Interpolation Method

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

Formosa Journal of Applied Sciences (FJAS)
Vol. 2 No. 6 (2023): June 2023

In March 2020 the World Health Organization stated that the Corona Virus pandemic (Covid-19) was due to its massive spread and hit all countries in the world. Academics and practitioners are called upon to carry out research activities in order to obtain a mathematical model that can be used to predict the number of people exposed to Covid-19 or other diseases. The researchers previously tried research to predict the number of people exposed to Covid-19 from early 2021 using the Monte Karlo method, the Hybrid Nonlinear Regression Logistic– Double Exponential Smoothing method, the Arima method, the BackPropagation and Fuzzy Tsukamoto methods, the K-Nearest method. Neighbors, Time Series Analysis method, Winter Method and Long Short Time Memory (LSTM) Artificial Neural Network method.