The Crop Price Prediction Using Machine Learning: Preliminary Stage

Ramya, T.K. and Shreedhara N, Hegde and Mohd Norshahriel, Abd Rani (2024) The Crop Price Prediction Using Machine Learning: Preliminary Stage. Journal of Data Science, 2024 (09). pp. 1-8. ISSN 2805-5160

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Abstract

The objective of our research is mostly concerned with agriculture. Farmers are the key players in agriculture. Knowing how much a crop will cost will enable you to make smarter judgments, which will reduce the losses and lower the risk of price changes. An ML model that forecasts agricultural prices in advance while accurately analyzing the crop may be able to solve this issue. A predictive system, a statistical method combining machine learning and data collecting, is used in many applications, including healthcare, retail, education, and government sectors. Its usage in the agriculture sector has comparable relevance. The back-end predictive model for this project is created utilizing machine learning algorithms. The steps involved in creating a predictive model are data collecting, data cleaning, data mining, and validation. The goal is to give farmers an intuitive user interface, and this model should correctly forecast crop market value given the real-time variables provided.

Item Type:	Article
Uncontrolled Keywords:	Crop Price Prediction, Random Forest Algorithm, Machine Learning Model.
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	24 Jun 2024 05:35
Last Modified:	06 Aug 2024 06:20
URI:	http://eprints.intimal.edu.my/id/eprint/1925

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