IMPLEMENTASI DATA MINING MENENTUKAN MEREK CELANA DALAM YANG PALING BANYAK DIPAKAI DI KELAS 14.1A.01 DENGAN ALGORITMA APRIORI

Abstract

Sales of apparel products, especially clothing pants in both men and women is increasing every month, the products offered are a variety of brands, brands that have influenced people to buy the product, to know the brand with enthusiasts most in need algorithms priori to be informed, by the algorithm most enthusiasts can be known. Priori algorithms including the type of association rules in data mining. One association analysis stage, which attracted many researchers to produce an efficient algorithm is the analysis of patterns of high frequency (frequent pattern mining). Important or not an association buffer in the know with the two benchmarks, namely: support and confidence. Support (support value) is presenting a combination of those items in the database, while confidence (rated capacity) is a strong correlation between the item and the association rules priori algorithms can help determine specialization within a class or group. It can be concluded that the algorithm can facilitate researchers apriosi for producing output accurately measured by the value of the value that has been set. Brand briefs value of the support is 50%, and the results of research can be generated value confidencenya 80% for the brand GT-Man dah Crocodile, while for underwear women value the support of 50% and the results of the research can be generated value confidencenya 84% for the brand Sorex and other brands in interest. From these data states that more men wear brand GT-Man and women brand Sorex.