CLUSTERING WITH SKATER METHODS AND UTILIZATION OF LISA ON UNEMPLOYMENT RATE
Abstract
Spatial cluster analysis is an analysis used to identify a spatial pattern or geographical grouping of data. One method that can be used in spatial cluster analysis is Spatial Cluster Analysis by Tree Edge Removal (SKATER). This research aims to analyze the spatial pattern of the Unemployment Rate in East Java by utilizing the SKATER method. The clustering results are then used to create a weighting matrix, which is used to find local spatial autocorrelation values using the Local Indicators of Spatial Association (LISA) index. The data is taken from BPS East Java with variables including unemployment rate, education level, minimum wage, Human Development Index, and population density. The results show that this approach is able to identify significant local spatial patterns. However, the selection of the number of clusters and input variables proved to be very influential on the results, so care needs to be taken.
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