Forecasting the Total of Paddy Production in Indonesia Using Time Series Regression Model

Abstract

Time series regression (TSR) is a forecasting model that can be used when there are trend and seasonal patterns. Paddy is a source of rice, which is a staple food for the Indonesian people. Paddy has a seasonal pattern because its cultivation depends on the rainy season. This study forecasts the amount of paddy production in Indonesia based on monthly data of paddy production in Indonesia to determine the production of paddy in 2023 and to assess the ability of the TSR model to forecast paddy production. The results showed that paddy production in 2023 is forecasted to have the same seasonal pattern as in previous years and reaches its peak production in April at 8.699 million tons. The TSR model of paddy production has a mean absolute percentage error (MAPE) of 8.654% indicating a very good forecasting accuracy.