000			a
999			_c22740 _d22740
003			OSt
005			20250429093701.0
008			250429b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_925987 _aVikranth, K.
245			_aPrice prediction system – a predictive data analytics using arima model
250			_aVol.14(3), Jan
260			_aChennai _bICT Academy _c2024
300			_a3304-3310p.
520			_aIn 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.
650		0	_94622 _aComputer Engineering
700			_926024 _aNethravathi, P. S.
773	0		_tICTACT Journal on Soft Computing (IJSC) _dChennai ICT Academy
856			_uhttps://ictactjournals.in/paper/IJSC_Vol_14_Iss_3_Paper_10_3304_3310.pdf _yClick here
942			_2ddc _cAR