IMPLEMENTASI ALGORITMA APRIORI DAN ALGORITMA CT-PRO PADA MARKET BASKET ANALYSIS; IMPLEMENTATION OF APRIORI ALGORITHM AND CT-PRO ALGORITHM IN MARKET BASKET ANALYSIS

Sonca, Riefka, Nur Rokhman

2015 | Skripsi | FMIPA

The increasingly widespread of modern retailing lead to the fierce competition among the modern retail. The owner of retail have to compete each other to gain customers, so the owners are forced to perform improvement in many aspects. One of improvement that can be done is to process the transaction data to find out the trend which prevalent to occur. One effective method which can be used to find the trend is by using data mining method. Apriori algorithm is the basic method to perform data mining. The principal of Apriori algorithm is if the itemset are often arises, then the whole subset of the itemset must also be frequently appears (Apriori property). By performing repetitive checking, then the time required to complete the method will be doubled. A method is proposed to solve the problem of Apriori method, which is by applying Tree algorithm. It is expect that by applying Compressed Tree the completion time can be reduced. It can be done since it is not necessary to repetitively check the subset of each frequent itemset. In the research conducted, proven that compressed Tree method were excellent to solve the problem of execution time. The execution time required were relatively much faster for the same result of association rules generated by Apriori method. Compressed Tree method also has anti-monotone property characteristic which is touted as a better method compared to Apriori method.

Kata Kunci : Data Mining; frequent pattern; Apriori; CT-Pro; Compressed Tree; FPGrowth; Algoritma Association rule.