VOLATILE FOOD PRICES FORECASTING MODELS FROM LIVESTOCK PRODUCTS IN JAMBI PROVINCE OF INDONESIA

Abstract

The method used in this research is a quantitative descriptive method using secondary data in the form of weekly data on prices of volatile food products from livestock in the form of beef, chicken meat, and chicken eggs for the period 2018 to 2021 sourced from the National Strategic Food Price Information Center. This research uses the Autoregressive Integrated Moving Average (ARIMA) model analysis, ARCH (Autoregressive Conditional Heteroscedasticy) model and GARCH (Generalized Autoregressive Conditional Heteroscedasticy) model analysis. The model for forecasting the price of volatile food products from livestock in the form of chicken meat, beef, and chicken eggs in traditional markets in Jambi Province, namely GARCH (1,1), has excellent performance. It is suggested that the GARCH (1,1) model can be used to forecast the prices of volatile food products from livestock in the form of chicken meat, beef, and chicken eggs in traditional markets in Jambi Province.

Keywords

• volatile food
• livestock products
• price