Penentuan Rencana Strategis Penjualan Fashion Melalui Penerapan Data Mining Untuk Pengelompokan Market Share Penjualan Fashion

Odi Nurdiawan, Riyan Suryatana


Changes in consumer thinking patterns have a huge impact on several companies engaged in e commerce. Every company engaged in e commerce has several ways to attract consumers to be interested in a product created by the company, one way is to classify consumer desires. The group examined in this paper is to group fashion interests from several desires. Diverse grouping through the application of data mining with clustering methods that determine the number of clusters then allocate data into clusters after that calculate the average of the data that is in each cluster after that allocate each data to the closest average, and if still there is data that moves clusters or changes in average values then returns to calculate the average. The results of this paper can classify the desires of consumers from the desires that consumers want. This research can classify the types of fashion, and can increase sales profits through these types of desires, then improve marketing or to restore goods.


Key Word: Fashion, Data Mining, clustering

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