Classification of Agriculture Area based on Superior Commodities in Geographic Information System

Research carries a classification model that combines LQ analysis and hierarchical classification using a single linkage. The classification results are a basis for mapping the potential of agriculture areas based on superior food commodities in Merauke Regency, Indonesia. LQ analysis is used to select food commodities. In contrast, the application of single linkage uses the production of three features, rice, corn, and peanuts, which have an LQ value>1, to group sub-districts based on agricultural potential. Intelligent mapping is represented by mapping the sub-districts agricultural areas according to the cluster. The classification results show that the first cluster has sixteen sub-district members, the second consists of three sub-districts, and the third cluster consists of one sub-district. Each cluster member has similarities based on the distance measurement with the smallest value using the Euclidean distance. The proposed classification model is a creative idea to map agricultural areas, which can present information on regional potential based on superior food crop commodities.

@article{Sumaryanti2022,
  title     = {Classification of Agriculture Area based on Superior Commodities in Geographic Information System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {10},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Lilik Sumaryanti and Rosmala Widjastuti and Firman Tempola and Heru Ismanto},
  doi       = {10.14569/IJACSA.2022.0131015},
  url       = {https://doi.org/10.14569/IJACSA.2022.0131015}
}