Penerapan Teknik Clustering Sebagai Strategi Pemasaran pada Penjualan Buku Di Tokopedia dan Shopee

Wiga Maulana Baihaqi, Kuat Indartono, Syifaul Banat

Abstract


Pustaka Aysha is one of the online bookstores in Shopee and Tokopedia. Shopee and Tokopedia are online shopping sites that are top ranked in Indonesia. The amount of competition that exists between stores so that requires a marketing strategy. This research uses clustering techniques in data mining marketing strategies. Clustereing is one technique in data mining to find data sets that have similarities with other data or data dissimilarity with others. The clustering process is carried out using k-means and k-medoids on the sales transaction data of the Pustaka Aysha bookstore in Shopee and Tokopedia on March 2019 and consists of each of the 488 data divided into 3 clusters namely the first cluster for the most product in demand, the second cluster for products that are quite popular and the third cluster for products that are of little interest. Both of these algorithms will be clustered evaluation to find out which algorithm has better performance in this research, the evaluation process is carried out using davies bouldin index to maximize inter cluster distance and minimize intra cluster distance, so the results obtained that the k-medoids algorithm have performance better than k-means.

Keywords


marketing strategy, clustering, k-means, k-medoids, davies bouldin index

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DOI: https://doi.org/10.31294/p.v21i2.6149

ISSN2579-3500

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

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