Perfilamiento territorial de municipios colombianos según su producción agrícola mediante análisis de conglomerados
DOI:
https://doi.org/10.17081/invinno.14.1.8527Palabras clave:
inteligencia artificial, aprendizaje automático, procesamiento de datos, k-means, producción agrícolaResumen
Objetivo: El objetivo principal de este estudio es clasificar y agrupar la producción agrícola de los municipios de Colombia para perfilar territorialmente las regiones y orientar el diseño de políticas económicas que promuevan su desarrollo. Se utilizaron los datos de las Evaluaciones Agropecuarias Municipales (EVA) del Ministerio de Agricultura y Desarrollo Rural, que contienen información histórica de la producción a nivel municipal.
Metodología: Se aplicó la metodología CRISP-DM, integrando la pre-paración de datos EVA con normalización Z-score y modelado mediante K-Means. El número óptimo de grupos se determinó mediante el método del codo y la cohesión se evaluó con el coeficiente de silueta para validar el perfilamiento territorial.
Resultados: Los resultados ofrecen información clave sobre las preferencias productivas del país, el potencial de desarrollo de cada territorio y las desigualdades existentes entre regiones. Se evidencian patrones de cultivo regionales diferenciados que resaltan la necesidad de estrategias agrícolas adaptadas a cada contexto local para mejorar la producción y satisfacer la demanda.
Conclusiones: El análisis identificó 10 perfiles agrícolas, mostrando que la mayoría de los municipios se agrupan en cultivos de ciclo corto, mientras que grupos específicos resaltan la especialización regional en productos de exportación.
Citas
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