Implementasi Association Rules Untuk Market Basket Analysis Pada Toko “Hanael Embroidery”

Dimas Pangestu(1*), Viddi Mardiansyah(2),

(1) Universitas Widyatama, Bandung, Indonesia
(2) Universitas Widyatama, Bandung, Indonesia
(*) Corresponding Author


The extremely tight competition in the business world means that business people must consider the best strategies to face competition. The most appropriate and competitive strategy now is to use information technology. The Hanael Embroidery Shop wants to increase the sales of its products so that it can be taken into account by other business competitors. In its daily life, the Hanael Embroidery Shop employs administrative staff to manage product sales and find the most sold products. Determining the layout and combination of goods based on consumer purchasing tendencies is one of the shop's solutions in developing the right marketing strategy to increase sales. This shop needs an application that can display product sales reports, making it easier for shop selectors to determine the proper promotion for the product. This paper will test the use of data mining using the Apriori Algorithm method to find the frequency of itemsets in a data set. A priori algorithm method that can adjust input values according to the criteria for items that have predetermined support and confidence values. The Apriori algorithm is a data mining algorithm that can be used in association rules to determine frequent itemsets that function to help find patterns in data. By using the Apriori algorithm, we obtained a group of shop products that are frequently purchased by customers, namely "Salvia Sweater", "Hoya Sweater", and "Lupine Clutch Bag Embroidery". This association is obtained with a minimum support value of 10% and a confidence value of 20% from 357 transactions. Based on the results of the tests that have been carried out, the designed application is successful. It can provide input and information on product combinations that shop customers often purchase.

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