Market Basket Analysis to Identify Customer Behaviours by Way of Transaction Data

Knowledge Engineering and Data SciencePublished 31 December 2017Open access

Fachrul Kurniawan, Binti Umayah, Jihad Hammad, Supeno Mardi Susiki Nugroho, Mochamad Hariadi

DOI10.17977/um018v1i12018p20-25

Citations46

TL;DR

The trial result showed that the development and the implementation of market basket analysis application through association rule method using apriori algorithm could work well and could be used to analyze the existing transaction data.

Abstract

Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of following the existing steps on data mining technique. The trial result showed that the development and the implementation of market basket analysis application through association rule method using apriori algorithm could work well. With the means of confidence value of 46.69% and support value of 1.78%, and the amount of the generated rule was 30 rules.

Keywords

Computer Science

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