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

Abstract

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 subdistricts agricultural areas according to the cluster. The classification results show that the first cluster has sixteen subdistrict 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.

Analysis of Regional Potential in Merauke Regency Based on Superior Livestock Population Using a Hybrid Algorithm

“…Hierarchical grouping uses a hierarchical (level) arrangement model in the data set based on the characteristics of the data [7], which are then grouped into a cluster [8]. The hierarchical method groups the training data into a cluster tree structure called a dendrogram [9]. The combination of the desertification mapping model and hierarchical analysis shows that different work units with the same level of desertification severity require other management decisions [10].…”