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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Muhammad Sahid
Universitas Padjadjaran
Mathematics

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Consensus Bayesian Network Learning for Market Basket Analysis in Indonesian Retail Transactions Muhammad Sahid; I Gede Mindra Jaya; Restu Arisanti
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.41879

Abstract

Understanding relationships among products in retail transactions is essential for supporting strategic decisions such as product placement and cross-selling. However, traditional market basket analysis is limited to pairwise associations and cannot capture complex conditional dependencies among multiple items. This study addresses these limitations by applying a Bayesian Network framework to model product relationships probabilistically. Transaction data collected over one month were transformed into a binary dataset of 441 transactions across 31 product categories. The network structure was learned using a stochastic search algorithm with a Bayesian Dirichlet equivalent (BDe) score, enhanced by a multi-seed strategy and edge support aggregation to ensure robustness. Parameters were estimated using maximum likelihood. The results indicate that relationships are both directional and context-dependent, with snack probabilities increasing with instant noodles but decreasing when cigarettes are also present. The LOIO accuracy is 0.6659.
Co-Authors I Gede Mindra Jaya Restu Arisanti