Menemukan Pola Temporal Rule Pada Data Penjualan Dengan Metode Temporal Association Rules
Edy Prayitno 26 Januari 2017 Sistem Informasi

Abstract / Intisari :
Abstract Sale data in a supermarket may be processed into information containing knowledge useful for managers in decision making. The information type examined in the study related to the temporal function of inter-item association represented one of the functions in data mining. The time used in the study was the transaction date. The study used Apriori algorithm to find the candidates of the frequent itemset that met the existing support count requirements. Subsequently, the frequent itemset meeting the support count requirement was processed using the method of temporal association rules. The results of the test using the parameter of minsup 0.1 and minconf 0.2 showed that the number of the temporal rules in the intervals of 9 months, 9 months and 14 months was the same for member data. There was not any temporal rule in non-member data for all intervals. The results of the definition of minsup 0.01 and minconf 0.05 for the intervals of 14 months, 9 months and 5 months showed that there was an increase in the number of the temporal rules in both the member and non-member data. Keywords: sale, temporal association rules, apriori and data mining.

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