Knowledge Engineering and Data Science


Market Basket Analysis to Identify Customer Behaviorsby Way of Transaction Data

Kurniawan, Fachrul (Unknown)
Umayah, Binti (Unknown)
Hammad, Jihad (Unknown)
Nugroho, Supeno Mardi Susiki (Unknown)
Hariadi, Mochammad (Unknown)



Article Info

Publish Date
30 Jun 2018

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.

Copyrights © 2018






Journal Info

Abbrev

publication:keds

Publisher

Subject

Computer Science & IT Engineering

Description

The journal welcomes experimental and theoretical findings on data science and knowledge engineering along with their applications to real-life ...