Forecasting Tapioca Production in Kollam, Kerala: An Arima Time Series Approach

Abstract

Tapioca is a type of flour extracted from the sugarcane root, so it is essential for most sectors, ranging from agriculture to food systems. Estimation of actual production for tapioca is very important not only to farmers but also to policymakers and companies relying on its supply. This research paper explored the use of ARIMA model for the prediction of tapioca output in Kollam district, Kerala. This is one of the most popular time series forecasting methods applied to agricultural applications because it is appropriate for replicating data patterns which include seasonal fluctuations. The study uses the production data from year 2001 to 2020. Considering the time series properties of data, such as autocorrelation and stationarity, it is found that the best fit model for forecasting would be the ARIMA (5,1,1) because it’s the model with significant goodness-of-fit indicators.

Cite as:

Riya Naik. (2024). Forecasting Tapioca Production in Kollam, Kerala: An Arima Time Series Approach. Journal of Applied Mathematics and Statistical Analysis, 6(1), 8–18. 

https://doi.org/10.5281/zenodo.14443923