Application of Association Rule Mining Method Using Apriori Algorithm to Determine the Purchasing Pattern of Home Made Dimsum - Pratama, Ekki; Abdi, Mahardika (Journal of Technology and Computer, 2024)
Dimsum Homemade's marketing strategy in the culinary field is one of them by increasing innovation in dimsum variants. However, some Homemade Dimsum business actors have shortcomings in understanding the purchasing patterns of dimsum products because there are too many variants of dimsum today. Dimsum Homemade business actors should know the most popular dimsum variants. This relates to the availability of which dim sum stock is the most so as not to experience large losses. So in this case technology is needed related to the dimsum variant purchase pattern algorithm so that sales data accumulates properly and it is easy to find out which dimsum variants are in great demand. One of the solutions needed is to apply the Association Rule Mining method using the a priori algorithm calculation. Application of Association Rule Mining (association rules), which is a data mining technique to find association rules for a combination of items. Based on the description of the problem above, the purpose and objectives of this study are to apply the Association Rule Mining method using the apriori algorithm to make it easier to analyze which dim sum variants have a high level of sales together. Thus the results obtained can be used to help make decisions in increasing accurate stock inventory and better product promotion. Association rules with apriori algorithm calculations can result in Homdemade dimsum purchase patterns, namely there are several association rule patterns that have a fairly high support and confidence value. For example, it is stated that the “Shrimp” dimsum menu has a tendency to buy the “Chicken” dimsum menu and vice versa. Then the “Chicken” dimsum menu becomes a menu associated with other dimsum menus, although the support and confidence values vary.