Predictive  Trends  of  Agricultural  Food  Commodities Prices in Indonesia: A Comprehensive Study using Time Series Forecasting

Muhammad Ali Yafi; Mutiara Ria Despita Maharani; Nur Afra Nabilla; Amanda Sekar Adyanti

doi:10.22146/ae.104454

Predictive Trends of Agricultural Food Commodities Prices in Indonesia: A Comprehensive Study using Time Series Forecasting

https://doi.org/10.22146/ae.104454

Muhammad Ali Yafi^(1*), Mutiara Ria Despita Maharani⁽²⁾, Nur Afra Nabilla⁽³⁾, Amanda Sekar Adyanti⁽⁴⁾

(1) Master of Sains Agribusiness, Faculty of Economics and Management, IPB University
(2) Master of Sains Agribusiness, Faculty of Economics and Management, IPB University
(3) Master of Sains Agribusiness, Faculty of Economics and Management, IPB University
(4) Master of Agribusiness, Faculty of Agriculture, University of Jember
(*) Corresponding Author

Abstract

Price uncertainty in food commodities will have an impact on people's food consumption. Prediction of future prices is necessary to serve as a policy reference in overcoming price fluctuations. The purpose of the study is to predict the prices of major agricultural food commodities in Indonesia for the period 2023-2029. The research uses time series data from 1990-2022 with price variables of maize, onion red chilli, beef, and chicken. The analytical tool used to answer the research objectives is the Autoregressive Integrated Moving Average (ARIMA) model. The results of the Augmented Dickey-Fuller (ADF) test analysis show that all variables have a significant level of 0.05 which indicates that the variables are stationary. The best model for forecasting prices by considering the AIC and SC values is the ARIMA models on maize commodities (1,1,0), shallot (2,1,0), red chilli (0,1,1), beef meat (0,1,1), and chicken meat (1,1,1). The prediction results of Indonesia's agricultural food commodities demand prices in 2023-2029 as a whole on the five commodities show a linear increase every year. Several factors that cause price increases are production disruptions due to extreme weather, high meat consumption on certain holidays, declining cattle populations, and high consumption of fresh meat compared to imported meat.

Keywords

ARIMA, Agricultural Food Commodities, Price Forecasting, Price.

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DOI: https://doi.org/10.22146/ae.104454