<![CDATA[This dtudy aims to determine the comparison of the performance of two methods, namely K-Means and K-Medoids. The performance of both is based on Sum Square Error (SSE) value. Both methods were used to group geothermal hotspot data on the island of Kalimantan. The geothermal point dataset used was obtained from the official NASA website. The parameters used are latitude, longitude, bright_ti4, scan, track, bright_ti5 and frp. In this study, it was carried out with variation in the value of k = 2, 3, 4, ...,12. Then the Elbow method was used to determine the optimal cluster of both methods. Based on the results, K-means provides greater group variation and better SSE values than the K-Medoids method on the optimal number of clusters. However, overall the results showed that K-Medoids had a better average SSE value than K-Means.Keywords: Clustering, K-Means, K-Medoids, Geothermal Hotspot]]>
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