Abstract

Abstract: In India, the agricultural sector faces rigorous challenges in order to optimize crop productivity. More than 60 percent of the crop also relies on rainfall from the monsoon. Recent advances in agricultural information technology have become an interesting area of study for forecasting crop yields. A major problem that remains to be solved based on available data is the problem of yield prediction. The best options for this reason are data mining techniques. In agriculture, various data mining techniques are used and evaluated to predict the output of crops for the future year. A short study of the prediction of crop yield using data mining algorithms is provided in this project. Agriculture is not as our forefather's did in today's existence. Owing to many factors, such as global warming, the strong climate changes create difficulties in interpreting climatic conditions. Thus, farmers are unable to understand which crop to pick to enhance yield. By using these data mining systems to understand soil and climate conditions, farmers would be able to take the right crop to the right place to increase yields. In volatile climatic conditions, it is therefore easy for farmers to determine which crop to take. Using data mining algorithms, this project will help solve these farming issues. It is possible to use algorithms such as SVM and Naive Byes.Keywords: Agriculture, Crop Prediction, Data Mining, Navie Byes, Farmer, etc.