Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Menganalisa Penjualan Rumah Parfume

Abstrak

store is a shop that offers various types of perfume scents under the IM brand. Even though it provides a wide range of choices, not all types of perfume sell quickly, some are in demand and some are less desirable. Data on sales, purchases and expenses at the store is irregular, so that the data only functions as an archive without being used for developing marketing strategies. The data that has been collected should be used as a decision-making system to solve business problems. To achieve this, the authors designed a data mining application in this study with the hope of providing maximum and effective results in analyzing perfume sales at the IM Parfume Rantau prapat store. The application of Data Mining with the K-Means Algorithm is proven to provide the best analysis and be a solution in developing the perfume business. Through clustering modeling with the K-Means algorithm and by dividing the number of clusters into 3, rapid miner succeeded in forming three clusters, where cluster 1 consisted of 9 products, cluster 2 had 3 products, and cluster 3 had 13 products out of a total of 25 product items observed.