Paddy Yield Prediction Model Using Data Mining Techniques

Abstract

Prediction of agriculture yield is a job that requires unification of knowledge from several areas such as data mining, statistics and agriculture. Subject of crop Yield prediction has been very popular among various organizations working in agriculture, producers, etc. Prediction of crop yield helps in managing the storage of crops as well as it directs the transportation decisions, and risk management issues related to crops. Data mining focuses upon methodologies for extracting useful knowledge from data and there are several tools to extract the knowledge that is it is a proficiency of examining the dataset such that the end results can be deduced easily and rapidly from the dataset. Knowledge gathered can be used to forecast the paddy yield. We collected the data from different government organizations, after preprocessing of data applied k nearest neighbor algorithm using Data Mining using soil nutrients, fertilizers nutrients, rainfall and temperature.