TELKOMNIKA Telecommunication, Computing, Electronics and Control
Frequent pattern growth algorithm for maximizing display items

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Frequent pattern growth algorithm for maximizing display items

Data mining
Display items
Frequent pattern growth

Products are goods that are available and provided in stores for sale. Products
provided in stores must be arranged properly to order to attract the attention of
consumers to buy. Products arranged in a store will depend on the type of store.
The product arrangement at a retail store will be different from the product
arrangement at a clothing store. Store display will reflect a picture that is in
the store so consumers know the types of products sold by product
arrangement. An attractive arrangement will stimulate the desire of consumers
to buy. In data mining there are several types of methods by use including
prediction, association, classification and estimation. In the prediction method
there are several techniques including the frequent pattern growth (FP-growth)
method. FP-growth algorithm is the development of the apriori algorithm. So,
the shortcomings of the apriori algorithm are corrected by the FP-growth
algorithm. FP-growth is one alternative algorithm that can be used to
determine the set of data that most often appears (frequent itemset) in a data
set. Results of research on the application of the FP-growth algorithm to
maximizing the display of goods. It is hoped that this research can be used to
adjust the product layout according to the level of frequency the product is
sought by the customer so that the customer has no difficulty finding the
product they want.

Asyahri Hadi Nasyuha, Jalius Jama, Rijal Abdullah, Yohanni Syahra, Zulfi Azhar, Juniar Hutagalung, Buyung Solihin Hasugian

http://journal.uad.ac.id/index.php/TELKOMNIKA

Aug 29, 2020

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