An Application of Time Series ARIMA Forecasting Model for Production of Sugarcane in India

This research examines the use of the Autoregressive integrated moving average ARIMA, time series forecasting model to anticipate sugar cane production in India. Sugar cane cultivation is a critical agricultural industry in India, impacting both economic and social trends. The ARIMA model is used because of its ability to detect and predict trends, seasonal fluctuations and other temporal patterns in data. The ARIMA model is trained and validated using historical production data for sugar cane in India. The study’s goal is to assess the model’s accuracy and dependability in projecting future sugar cane production patterns, allowing stakeholders to make educated decisions about agricultural policy, and economic planning. The results indicate the efficiency of ARIMA in projecting sugar cane output, emphasising its potential as a helpful tool in agriculture forecasting and planning