<![CDATA[With the Covid 19 which has hit the last few years, sales in various fields have a negative impact, including Supermarket X, which has experienced a decline in various branches in various regions. For consideration, they evaluate the sales of these branches. By classifying the existing sales data, it is hoped that they will be able to see which self-service branch group x is not doing well, which one is already good. However, it is necessary to have a good classification technique so that evaluations are carried out based on good calculation results. Therefore, the author tries to use the K-Mean Algorithm and the AHP Algorithm to classify the existing sales data. The K-Mean Algorithm and the AHP Algorithm are algorithms that are able to cluster a set of data. By clustering the stores based on the proximity of the sales results for the last 2 years which has gone up and down using these 2 algorithms, we will be able to see which stores are classified as good and which are not. Based on the comparison results from the calculation results, it was found that the best results were using the K-Mean algorithm with k2 in the 3rd literacy with a ratio of 0.04926]]>
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