1Department of Computer Science, Periyar University Constituent College of Arts and Science, Pennagaram, Dharmapuri-636 803, Tamil Nadu, India
2Department of Computer Science, Govt. Arts College for Women, Krishnagiri-635 001, Tamil Nadu, India
*Corresponding Author: K. Samundeeswari, Department of Computer Science, Govt. Arts College for Women, Krishnagiri-635 001, Tamil Nadu, India, Email: samun.npgs18@gmail.com
Online published on 22 July, 2021.
Crop yield prediction is an important issue for the proper selection of crop for sowing. Earlier prediction of crop is done by the farmer's experience on a particular type of field and crop. Predicting the crop is done by the farmer's experience based on the factors like soil types, climatic condition, seasons and weather, rainfall and irrigation facilities.
Data mining techniques is the better choice for predicting the crop. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. This research proposes and implements a system to predict crop yield from soil data. This is achieved by applying Decision Tree Algorithm on agricultural data. The main aim of this research is to pinpoint the accuracy of Decision Tree Algorithm and C 5.0 algorithm which is used to predict the crop yield.
This paper presents a brief analysis of Crop yield prediction using data mining technique based decision tree algorithm and C5.0 algorithm for the selected region (Krishnagiri) district of Tamil Nadu in India. The experimental result shows that the proposed work efficiently to determine the accuracy of decision tree algorithm and also to predict the crop yield production using R-Tool.
Crop yield prediction, Data mining, Decision tree algorithm, R-Tool, Soil data set
