In India, agriculture represents the primary occupation of more than
60% of the population. In terms of GDP, economic growth, traditional
aspects, and social aspects, agriculture is essential for the country's
development. The Indian farmers experienced numerous issues that
have an impact on their way of life because the expansion in the
agronomy business has not been as expected during the past two
decades. Price fluctuation is one of the major issues faced by farmers,
and as a result, they cannot get a reasonable price for their commodity.
Also, it is very problematic to decide today without knowing the future
price. So, this paper focused on finding a solution to the uncertainty
problem in price faced by farmers that helps them take appropriate
decisions during the farming process. The paper mainly concerns
predictive data analytics using the ARIMA model, which predicts the
price of areca nut products for the next 4 years using the past ten-year
price dataset. The ARIMA model is a time series approach and a very
appropriate framework for predicting future prices compared to other
models. This paper includes a step-by-step procedure for the ARIMA
techniques for forecasting price of agriculture commodity, and the
outcomes are represented in the form of tables and graphical
representations.