Mapping is one of the steps that is useful for monitoring changes in water quality, planning and management, increasing public awareness, and analyzing the impact of climate change. This study aims to obtain river water quality mapping through statistical clustering methods, namely grouping observation points to points with excellent and bad quality are obtained. This research increases accuracy and efficiency in monitoring and managing water resources, thereby supporting more appropriate decision-making to preserve the environment in the area. This method is called Spatial Cluster Analysis by Tree Edge Removal (SKATER), which is a data grouping method that considers geographical aspects between observations. Obtained secondary data from The Special Region of Yogyakarta (DIY), which was then carried out statistical analysis using spatial cluster analysis with SKATER. The clustering results are then presented to the mapping. This study uses COD, pH, total phosphate, nitrate, and ammonia parameters at 43 river sample points in the DIY. SKATER produces 3 clusters, each consisting of 32 locations, 2 locations, and 9 locations. The results of the study showed that the cluster with the highest average COD was cluster 2, which was 29 mg/L and was located in the Winongo and Oya rivers. Likewise, phosphate, pH, and ammonia levels were higher than in other locations. The results are used as indicators for controlling pollution at these cluster points. This result is different from several similar studies that carried out clustering without considering the geographical aspects of the observations. This information is used as a reference for controlling pollution and reducing COD and other parameters at river locations. The challenge of adapting the SKATER method to different river characteristics limits research on rivers in the Yogyakarta region, and implementing the method requires technological support and expertise that do not yet fully exist in the region.