Optimización de la Productividad Agrícola Ecuatoriana: Un Análisis de Conglomerados basado en K-Means

Abstract

The research conducts an analysis of the Optimization of Ecuadorian Agricultural Productivity through Clustering based on K-Means, with the objective of identifying patterns and groupings in agricultural productivity data, paying special attention to the variables of harvested quantity and sold quantity. These variables are key measures to evaluate the production and commercialization of agricultural products. To carry out the cluster analysis of agricultural productivity in Ecuador, data from the Continuous Area and Agricultural Production Survey (ESPAC) of the National Institute of Statistics and Censuses (INEC), corresponding to the year 2022, were used, specifically focusing on permanent crops.The study results indicate that there is a marked difference in the variables of harvested quantity and sold quantity in cluster 3, where specific products such as bananas and soursop predominate. These products, which are predominant in cluster 3, demonstrate greater efficiency in production, achieving significantly superior results with the same or fewer resources compared to the other clusters. This finding suggests that bananas and soursop have high potential for improving the country's agricultural productivity. Furthermore, the analysis reveals that optimizing production and commercialization in these crops could be key to sustainable agricultural development in Ecuador. In conclusion, the use of clustering analysis based on K-Means has allowed the identification of highly efficient areas in Ecuadorian agricultural production, highlighting the importance of specific strategies for banana and soursop crops. These results provide a solid basis for the formulation of policies and the implementation of improved agricultural practices, which could significantly increase the productivity and sustainability of the agricultural sector in Ecuador.