Abstract
With the growth of technology and industry agricultural farming has been commercialized. Many industries are taking contract on the agricultural production, which is affecting the farmers economy. The influence for this could be higher demand for food, natural conditions such as soil, climate, water, etc., the lower price coated to the agricultural production, high market cost for the produced commodity, high charges on the cold storages, and also due to lack of proper marketing facilities available to the farmers. This forces farmers to sell their crops to the middle man or to reduce their production of the commodity they are into due to lack of proper estimation of the growth of the crops. Hence, in this paper, we analyze the price of potatoes through the Time Series Analysis using a price forecasting system that is implemented based on ARIMA Model. Here we aimed to forecast potato price for leading 10 years. The data used here is based on the monthly average potato price for past 10 years (2010–2019) of 5 different states in India i.e., Karnataka, Madhya Pradesh, Gujarat, Rajasthan, and Maharashtra. Based on the data collected, potato price at one major market for each state is analyzed using ARIMA model. Parameters considered were rolling mean and standard deviation, ADCF, PACF and ACF plots and also AIC. Model was examined by computing different measures of goodness of fit that best suites the value.
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Jamuna, C.J., Patil, C., Kumar, R.A. (2021). Forecasting the Price of Potato Using Time Series ARIMA Model. In: Kumar, S., Purohit, S.D., Hiranwal, S., Prasad, M. (eds) Proceedings of International Conference on Communication and Computational Technologies. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-3246-4_40
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