Abstract: Our countries economy is mainly based on agriculture. Farmers plays an important role in agriculture, At present scenario due to variation in climatic change and other price influencing parameter farmers face massive loss due to uncertainties in the price fluctuation. The developed crop price prediction and forecasting system helps farmers to predict price of the commodity. The system gives detailed forecast up to next 12 month .The methodology we use in the system is decision tree regression which is machine learning regression technique. The parameter considered for prediction are:- rainfall, wholesale price index (minimum support price, cultivation cost). Accurate prediction of crop price; plays important role in crop production management. Such prediction will also support the allied industries for strategizing the logistics of their business.
In general with help of this application farmers get a beforehand prediction which helps to increase their profit and prevent massive lose. Which in turn increase countries economy.
Keywords: Forecasting System, Decision Tree Regression, Price Prediction
| DOI: 10.17148/IJARCCE.2020.9306