<![CDATA[In 2020, the government conducted a Minimum Competency Assessment (MCA) for students in Indonesia's 5th, 8th, and 11th grades. However, the results of this MCA are still not satisfactory. This research aims to group an area according to the level of data similarity using the k-means clustering method with the categorization of the area into low, medium, and high. This study uses MCA result data on literacy and numeracy for each level of education. From each cluster formed, there are significant differences in characteristics based on testing from the Tukey and Analysis of Variance (ANOVA) test. From the categorization of the clusters formed, it's expected that the government needs to provide particular interventions in areas included in cluster 1, which consists of 19 provinces in Indonesia with the lowest AKM characteristic scores. The abstract must describe the entire content of the research or written work.]]>
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