PENERAPAN KAIDAH ASOSIASI PADA DATA TRANSAKSI MINIMARKET DENGAN MENGGUNAKAN ALGORITMA FREQUENT PATTERN GROWTH (FP-GROWTH)
Abstract: Transaction data are
stored only as many records can provide useful knowledge in making policies and
marketing strategies for the mini market KOCIKA UNESA in State University of
Surabaya Ketintang. For that purpose one can apply the techniques of DATA
MINING association rules. Association rules is a procedure to search for
knowledge in the form of consumer purchasing patterns. This pattern can be
input in making policy and marketing strategy. A pattern is determined by two
parameters, namely support (support value) and confidence (certainty value).
This association rules using frequent growth algorithm (FP-growth) by applying
the FP-tree data structure to find the purchase patterns. One pattern resulting
from the analysis of transaction data last 1 month with 23 categories of items
that if buy detergent, buy soap too with support = 19% and = 75% confidence value.
Penulis: GUNTUR WICAKSONO
Kode Jurnal: jpmatematikadd130963