Implementation Of Data Mining On Sales At Resto D'sdl Lembang Using Aprioric Algorithm Method

Abstract

This research was conducted to help determine the menu or package that is often purchased simultaneously. The priori algorithm is used to produce data mining regarding the determination of association rules which is carried out by calculating support and confidence in the sales of food menu mechanisms in a restaurant with a case study of the restaurant d'DSL Lembang. The resulting a priori algorithm will be implemented and tested with the Tanagra application. From the results of the discussion and data analysis carried out, it was found that with the application of the a priori algorithm in determining the combination between itemset with a minimum support of 60% and a minimum confidence of 90%, it was found in the initial calculation of the combination of one itemset, a combination of 2 itemset, a combination of 3 itemset and a final association rule with The highest value of support and confidence is if the consumer orders the Hot Sweet Tea menu, Chicken Driver Package and Liwet Rice at the same time with a support value of 58% and a confidence value of 100%.