The K-Means Clustering algorithm is applied to group similar farmer groups based on their characteristics, such as size, location, and crops cultivated. The results of the analysis are used to generate recommendations for the decision maker. The effectiveness of the proposed system is evaluated using real-world data and compared with a traditional method. The results show that the proposed system provides more accurate and reliable recommendations compared to the traditional method. The results of this study contribute to the development of a more efficient and effective allocation process for agricultural grants and can benefit both the government and the farmer groups in increasing agricultural productivity and sustainability.
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