<![CDATA[Abstract−Cassava is one of the main foodstuffs, not only in Indonesia but also in the world. In Indonesia, cassava is the third staple food after rice and corn. The spread of cassava plants extends to all provinces in Indonesia. Using data mining is one of the ideas of information to classify the amount of cassava productivity by province, by using the k-means clustering method the amount of cassava productivity will be collected based on the year (2011-2018) of 30 provinces. K-means is a method with unsupervised classification type where the data is grouped into one or more clusters. k-means modeling the dataset into clusters where one cluster has the same characteristics and has different characteristics from other clusters. This study aims to classify the amount of cassava productivity by province. Where the highest cluster results are obtained with a total of 2 provinces, medium cluster with 4 provinces, and a low cluster with 24 provinces.Keywords: Data Mining, K-means, Clustering, Cassava, RapidMiner Studio]]>
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