Penerapan Market Basket Analysis Data Mining Pada Penjualan Batik dengan Menerapkan Algoritma Apriori
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Gatot Soepriyono
*
Universitas Nasional, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
Batik is a cloth that is depicted by applying wax to the cloth and processing it in a certain way. In certain batik companies, there are products that are characteristic of that company. As time goes by, problems arise with the sale of batik due to lack of proper stock availability in shops, making it difficult for customers to order batik. This problem that occurs is certainly a problem that must be resolved. If the available stock of goods does not match the customer's wishes, the goods will be piled up in the shop's stock. Apart from that, if the customer does not find a batik model that suits his wishes, it will cause the customer to switch to another shop. The sales results are reported in the form of a ledger or entered into a computer. The report produced is a sales transaction data report. Data mining itself is a process of processing quite large amounts of data. In the future, the data recorded in the ledger can be used as information in determining business strategies for batik sales. Market Basket Analysis aims to manage customer data or sales data. The a priori algorithm is an association part of mining data. A priori algorithms can help in forming candidate item combinations. From the results of the research carried out, there is 1 combination of items that meets the support value of 30%, namely items T09 and T12, where the support value obtained is 30.76% and with a confidence value of 100%.
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