Comparison of the K-Means Algorithm and C4.5 Against Sales Data

In general, the process of collecting and grouping data requires a long process. And if it has to be grouped manually takes very time. Therefore, mining is solution for clustering - lot classify it. this research conducted at CV.Togu Togu On Medan Branch, applied using K-Means model C4.5 algorithm which provides standard in various fields used classification because results method easy understand interpret. . The K-means non-herarical an algorithmic technique items into k clusters by minimizing distance SS (sum square) cluster centroid. method, number can determined researcher himself. testing methods measure quality are Silhouette Coefficient Elbow Method. Based on conducted, there significant differences before after two methods. will compared with form rules (decision trees). This produces goods that have highest level sales/behavior