ISSN (Online) : 2456 - 0774

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ISSN (Online) 2456 - 0774



Abstract: In order to maximise crop yield in India, the agricultural sector faces significant obstacles. Rainfall from themonsoon is also essential for more than 60% of the crop. Recent improvements in agricultural information technology havepiqued my interest as a potential source of crop production forecasting data. The topic of yield prediction is a critical issuethat has yet to be solved using existing data. Data mining techniques are the greatest solutions for this reason. Various datamining approaches are utilised and analysed in agriculture to anticipate crop yield for the coming year. This projectincludes a brief analysis of agricultural yield prediction using data mining techniques. Agriculture now is not the same as itwas for our forefathers. Strong climate changes generate challenges in evaluating climatic conditions due to a variety ofvariables, including global warming. As a result, farmers are unable to determine which crop to plant in order to increaseoutput. Farmers would be able to take the correct crop to the right area to increase yields by using these data miningtechnologies to analyse soil and climate variables. Farmers can easily decide which crop to plant in the face of changingweather circumstances. This initiative will use data mining methods to assist in the resolution of various farming difficulties.SVM and Naive Byes are examples of algorithms that can be used.Keywords: Agriculture, Crop Prediction, Data Mining, Navie Byes, Farmer, etc

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