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All Journal Faktor Exacta JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information System, Applied, Management, Accounting and Research Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jejak digital: Jurnal Ilmiah Multidisiplin
Suranto Saputra
Universitas Indraprasta PGRI
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Analisis Association Rule Menggunakan Algoritma FP-Growth pada Dataset Online Retail Laksana Priyo Abadi; Heru Sulistiono; Suranto Saputra; Lusi Ariyani
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 5 (2026): AGUSTUS-SEPTEMBER
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/5ap2mr81

Abstract

Market Basket Analysis is widely used to identify consumer purchasing patterns from transaction data and support data-driven business decisions. This study aims to analyze product purchase patterns using the FP-Growth algorithm on the Online Retail Dataset obtained from the UCI Machine Learning Repository. The research employed a data preprocessing stage, including removing missing values, duplicate records, cancelled transactions, and invalid transaction values, followed by transaction transformation and one-hot encoding. The FP-Growth algorithm was implemented with a minimum support of 1%, while association rules were generated using a minimum confidence of 50%. The results produced 973 frequent itemsets, indicating that the algorithm effectively identified frequently purchased product combinations. The strongest association rule was found between REGENCY TEA PLATE PINK and REGENCY TEA PLATE GREEN, with a support value of 0.0109, a confidence value of 90.18%, and a lift value of 61.90. These findings demonstrate that FP-Growth is effective in discovering purchasing patterns and can support cross-selling, product bundling, shelf arrangement, and inventory management strategies in the retail sector.
Co-Authors abdul mufti Achmad Sarwandianto Adelia Tri Pramudya M Ardhi Dinullah Baihaqie Dinullah Baihaqie Aswin Fitriansyah Dina Rima Dhona Eddy Saputra Fajar Ramadhan Heru Sulistiono Laksana Priyo Abadi Lusi Ariyani Nahot Frastian Rayung Wulan Riri Indriyanti Yogi Bachtiar Yulianingsih Yulianingsih Zaenul Arifin