Asian Journal of Dairy and Food Research

SCOPUS
  • Year: 2025
  • Volume: 44
  • Issue: spl

Forecast Analysis of Corn and Cassava Production in North Sumatra Province, Indonesia

  • Author:
  • Rahmanta1,*, Siti Khadijah Hidayati Nasution1, Edi Warsito2
  • Total Page Count: 6
  • Page Number: 182 to 187

1Faculty of Agriculture, Universitas Sumatera Utara, Medan, Indonesia

2Office of Food Security, Food Crops and Horticulture of North Sumatra Province, Indonesia

*Corresponding Author: Rahmanta, Faculty of Agriculture, Universitas Sumatera Utara, Medan, Indonesia, Email: rahmanta@usu.ac.id

Online Published on 10 March, 2026.

Abstract

Fluctuations in food production, namely corn and cassava, from year to year tend to change, making food production forecasting quite important. Production movements greatly affect other sectors, so a method is needed to forecast future food production. The purpose of this study is to examine North Sumatra Province’s food production predictions.

The Central Statistics Agency and the Food Crops and Horticulture Agency provided the secondary data used in this study, which covered the years 1996-2022. Using the Eviews 13 program, the data analysis technique applies the ARIMA (Autoregressive Integrated Moving Average) method.

The results of the study indicate that in Langkat Regency, the best model for forecasting corn production is the ARIMA (1,1,0) model, with corn production experiencing moderate growth over the next decade, while the best model for forecasting cassava production is the ARIMA (2,1,2) model, with cassava production also experiencing growth. In Tapanuli Utara District, the best model for forecasting corn production is the ARIMA (2,1,2) model, with corn production expected to increase in the future. Meanwhile, the best model for forecasting cassava production is the ARIMA (2,1,1) model, with cassava production showing a slight decrease.

Keywords

ARIMA, Cassava, Corn, Forecasting, Production