• Anurag Chaudhary
• Pallavi B Vyas
• Ashish Vyas

As we know India is an agricultural country. At least 75% of its population lives in villages and work as farmers. India is one of the largest agriculture farming in the world. But in India farmer lives in poverty though he is the backbone of our country. They work very hard but in return gets a little amount of production of the crop. This is due to the change in the weather conditions, not only this farmer not getting proper platform from industries to sell their crops. It is very difficult for farmers to increase crop production in India. It is a very challenging task to achieve the desired targets in the production of crops. There are various factors are to be considered which will directly impact the productivity of the crops. Predicting crop is one of the important factors in agriculture. Farmer and industries should have information regarding the environment and soil before growing the crop in the fields and to achieve targeted crop production. Technology in the field of agriculture has increased in the past few years and data mining is one of the trending into the agriculture field. The main challenge of using big data in agriculture is the identification of the effectiveness of big data mining The present study gives an understanding of the various data mining methods applied to crop and to determine which crops will be best for a specific area or soil. Not only for farmers but for industries to predict the amount of the crops and providing a proper platform to farmers to sell their product at a reasonable amount and at a proper time.

Data Mining, Productivity

"Data Mining in Agriculture for Industry to increase Productivity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.462-466, January 2019, Available :http://www.jetir.org/papers/JETIRDW06077.pdf

"Data Mining in Agriculture for Industry to increase Productivity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp462-466, January 2019, Available at : http://www.jetir.org/papers/JETIRDW06077.pdf