Analisis Consumer Behaviour Pada Toko Retail Dengan Metode APRIORI-SD

Nathaniel Edward, Rolly Intan, Alvin Nathaniel Tjondrowiguno

Abstract


Retail store needs to evolve especially in digital age where ecommerce
becoming more and more common and most people
prefer the convenience of an e-commerce. One of the biggest
advantage of a “newer” e-commerce is they build they’re
business model on the foundation of processing data, whereas
older retail store doesn’t. Development of data mining and
machine learning are pushing older business model to do better.
This journal represents the possibilities of using subgroup
discovery as a method of analyzing transactional data. Subgroup
discovery is a data mining technique which extracts interesting
rule. APRIORI-SD is a method within subgroup discovery where
evaluation measure use by APRIORI-SD already prioritizing
unusualness distribution of a given data.
The result of this knowledge are able to find anomalies such as
differentiating subgroup(s) with differences up to 50% compared
to overall distribution percentage. With the result people are
able to create a better strategies in the future.


Keywords


APRIORI, APRIORI-SD, Subgroup discovery

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