Penerapan Algoritma FP-Growth dalam Penentuan Pola Pembelian Konsumen pada Kain Tenun Medali Mas

Abstract

In Kediri City there is a very popular woven fabric shop called Medali Mas. It has high sales transaction activity resulting in a large stack of data purchases. This data stack is examined as an information pattern for consumer purchases using data mining association rule techniques and FP-Growth algorithms. The FP-Growth algorithm uses the concept of development tree in searching for frequent item sets. The data used are, 26 types of woven fabric items and 200 transaction data provided that 2 or 3 types of items in 1 transaction. Determined  minimum support value of 20 percent and  minimum confidence value of 10 percent. It also used Chi-Square testing to find out how much correlation between variables from the results of frequent itemsets that have been calculated. The final result of the consumer purchasing pattern is obtained (m to no) when buying Semi sutra Lusi = grey, Pakan = Blue Flowers, then the consumer might buy Sarong Lusi = black, Pakan= green Lurik and Cotton Lusi= yellow, Pakan = Tosca Bamboo with the results of the correlation between variables at 19.1397274913.