<![CDATA[One method to study health patterns, including dental and oral health, is to use a spatial approach assisted by a Geographic Information System. Dental caries itself is one of the emerging dental and oral health problems. So this study aims to determine the pattern of grouping and the number of dental caries cases spatially. The grouping pattern or called spatial autocorrelation was analyzed using several spatial autocorrelation methods. The methods include analysis of Moran I, Getis-Ord Gi*, and LISA. While LISA stands for Local Indicator of Spatial Association. The research sample is 27 subdistricts within Ciamis District. The number of dental caries in 27 subdistricts ranges from 0 to 163 cases. From the results of the study, it is known that the Moran I index ranges from -0.625 to 0.763. It is known that 12 subdistricts have a Moran I value 0. While the Getis-Ord Gi* index range is from -1,438 to 5,175 with 12 subdistricts having a Getis-Ord Gi* value 0. Based on LISA analysis, it is known that there is a spatial autocorrelation and grouping with LISA classification goes into in the HH class covers 2 subdistricts. This means that in the 2 subdistricts the number of dental caries cases is known to be the highest, clustered, and has spatial autocorrelation compared to other sub-districts.]]>
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