Estimation of Major Agricultural Crop with Effective Yield Prediction using Data Mining
Rajesh Kumar Maurya1, Sanjay Kumar Yadav2, Tarun Kumar Sharma3
1Rajesh Kumar Maurya, Department of Computer Science and Information Technology, Sam Higginbottom University of Agriculture, Technology and Sciences Allahabad, India.
2Sanjay Kumar Yadav, Department of Computer Science and Information Technology, Sam Higginbottom University of Agriculture, Technology and Sciences Allahabad, India.
3Tarun Kumar Sharma, Assistant Professor, ABES Engineering College, Ghaziabad, Uttar Pradesh.
Manuscript received on 04 May 2019 | Revised Manuscript received on 09 May 2019 | Manuscript Published on 13 May 2019 | PP: 170-174 | Volume-8 Issue-7S May 2019 | Retrieval Number: G10340587S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Agriculture is an area where the at most uncertainty exist. Crop production is totally depended on number of factors like geography, weather, biological, political, and economical. Indian financial system is mainly driven by farming and provides service opportunity in farming sector of Indian financial system is higher than world’s average (6.4%). Agriculture (17.32%), Services (53.66%) and Industries (29.02%) are mainly contributing in the GDP of the nation.. Apart from this, a massive amount of raw agricultural data is present, but analysis these facts are very complicated for yield estimation of crop. So the most difficult task is to bring meaningful information and knowledge out of the raw agricultural data. Data mining can tailor data knowledge to estimate the crop yield. The aim of this research paper is to estimate crop yield by implementing data mining techniques.
Keywords: Statistical Approaches, DM Technique, Production Estimation, Tracking Patterns, Classification, Cluster Based Analysis, Linear Regression Analysis (LRA), Multiple Regression Analysis (MRA) using SPSS.
Scope of the Article: Classification