Abstract

A decision making for a long-term paddy grain and rice price guidelines need a future price prediction and a forecasting model that made based on time progression. The most popular model used is ARIMA. The common problem in forecasting the paddy grain and rice in Indonesia using this model was choosing the best model which fit all type of forecasting. This study aimed to determine the most appropriate ARIMA Model and forecast paddy grain and rice’s price on the farmer level, wholesale level, and international level. The prediction began after the stationary test and the best model selection conducted. The ARIMA model used was chosen by the lowest AIC and SC accuracy value. ARIMA Model used in this study were grain price on the farmer level (1,1,2), grain price on the milling level (1,1,2), rice price on the wholesale level (1,1,3), and rice price on the international level (3,1,7). The rice price prediction in the next sixth months on the farmer level was IDR 5,905.15/kg and the actual price was IDR 5,524.89/kg, on the milling level was IDR 6,014.35/kg and the actual price was IDR 5,641/kg, on the wholesale level was IDR 12,163.92/kg and the actual price IDR 12,115/kg, while the on the international level was US$ 462,065/Ton and the actual price was US$ 408/Ton. This study concluded that the price list at a different level of the market was requiring a different model of ARIMA.

Highlights

  • Rice is a staple food in Indonesia which is produced from paddy plant

  • Those facts indicated that rice contributed a major role in Indonesia, rice price stabilizing is required to be conducted by the government

  • According to the National Institute of Statistical Data, on the 136th month (April 2019) the paddy grain price decreases by 7.65% or reaches IDR 5,221/kg, and on the 137th month (May 2019) the price increases by 1.47% or reaches IDR 5,298/kg

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Summary

Introduction

Rice could be categorized as a strategic commodity politically. Rice plays a strategic role in strengthening the food, economic, and political security/stability in a country. A stable rice stock, price, and distribution are necessary for Indonesia. Those facts indicated that rice contributed a major role in Indonesia, rice price stabilizing is required to be conducted by the government. Forecasting technique is a solution offered to support the decision making in stabilizing the rice price (Mariska, 2016). A decision making using a forecasting technique required an estimation that could be analyzed through a time series analysis. ARIMA (Autoregressive Integrated Moving Average) Model is a univariate time series model use to forecast the price

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