IMPLEMENTATION OF STOCHASTIC TIME SERIES FORECASTING ARIMA MODEL FOR HORDEUM VULGARE PRODUCTION IN INDIA

Grown in a variety of environments, Hordeum vulgare (Barley) is the fourth largest grain crop globally, after wheat, rice and corn. This study analyzes with implementation of stochastic time series forecasting autoregressive integrated moving average (ARIMA) model for H. vulgare production in India based on H. vulgare production data during the years from 1961 to 2020. A decision is made on the appropriate ARIMA model for H. vulgare production in India based on Autoregressive (AR), Moving Average (MA) and ARIMA processes. The results examine ARIMA (0,1,2) and its components Percentage Error (MAPE), Normalized BIC and Box-Ljung Q statistics. H. vulgare production in India is predicted to increase from 107.86 million tons in 2019 to 113.10 million tons in 2025 according to the chosen model.