Mining Association Rules in Seasonal Transaction Data

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Nowadays global retail business faces new challenges due to changes in consumer buying preferences, likewise in Indonesia that consequence increasing level of competition among retailers. Moreover, Indonesia's government announced major reforms in foreign investment in 2016 which attracted international retailers. Therefore, local retailers have to plan a strategy to expand the current market through enhancement of customer satisfaction related to their purchasing activities. This research aims to analyze market basket data to help local retailers understand consumer purchase behavior by finding association pattern. Nevertheless, the retail industry is highly seasonal. Hence, there are three types of season in retail industry which were proposed as classification in this research, i.e. peak season, normal season, and slack season. Based on the result, each season has similarity in generated pattern among other seasons. However, there are also 6 unique patterns found from a certain season. By knowing the discovered association patterns in each season, the company may determine product offering or promotion strategy for different season.

Original languageEnglish
Title of host publicationProceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018
EditorsShaozi Li, Ying Dai, Yun Cheng
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages321-325
Number of pages5
ISBN (Electronic)9781538655009
DOIs
Publication statusPublished - 2 Jul 2018
Event5th International Conference on Information Science and Control Engineering, ICISCE 2018 - Zhengzhou, Henan, China
Duration: 20 Jul 201822 Jul 2018

Publication series

NameProceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018

Conference

Conference5th International Conference on Information Science and Control Engineering, ICISCE 2018
Country/TerritoryChina
CityZhengzhou, Henan
Period20/07/1822/07/18

Keywords

  • Apriori algorithm
  • data mining
  • market basket analysis

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