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

Fachrul Kurniawan (Dept. of Informatics Eng., Maulana Malik Ibrahim State Islamic Univ., Jl. Gajayana No.50, Malang 65144, Indonesia)
Binti Umayah (Dept. of Informatics Eng., Maulana Malik Ibrahim State Islamic Univ., Jl. Gajayana No.50, Malang 65144, Indonesia)
Jihad Hammad (ICT Faculty, AlQuds Open University, Beit Jalla-The Main road-Khallat Al Badd, Bethlehem, Palestine)
Supeno Mardi Susiki Nugroho (Dept. of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS,Surabaya 60111, Indonesia)
Mochammad Hariadi (Dept. of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Jl. Raya ITS,Surabaya 60111, Indonesia)

Knowledge Engineering and Data Science
Vol 1, No 1 (2018)

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.