Penerapan FP-Growth Dalam Market Basket Analysis Untuk Memahami Kebiasaan Belanja Konsumen
Article Sidebar
Main Article Content
Abstract
This study aims to analyze consumer purchasing patterns using Market Basket Analysis with the FP-Growth algorithm. The dataset consists of sales transaction data processed using RapidMiner. The research stages include data collection, preprocessing to handle missing values, frequent itemset mining using FP-Growth, and association rule generation. The results show that FP-Growth generated 25,871 frequent itemsets with a maximum size of 10 items and support values that meet the defined threshold. The resulting association rules exhibit confidence and lift values indicating strong relationships among products, where milk frequently appears as a key product associated with items such as chicken, magazines, low-fat yogurt, and frozen smoothies. These findings demonstrate that the application of FP-Growth using RapidMiner is effective in identifying consumer purchasing patterns and can support decision-making in sales strategies.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Alsaeedi, H. A., & Alhegami, A. S. (2022). An Incremental Interesting Maximal Frequent Itemset Mining Based on FP-Growth Algorithm. 2022. https://doi.org/10.1155/2022/1942517
Diaz, J. A., Dolores, G. M., Maria, R., & Bautista, J. M. (2023). A survey on the use of association rules mining techniques in textual social media. Artificial Intelligence Review, 56(2), 1175–1200. https://doi.org/10.1007/s10462-022-10196-3
Dwiputra, D., Widodo, A. M., Akbar, H., Firmansyah, G., & Unggul, U. E. (2023). EVALUATING THE PERFORMANCE OF ASSOCIATION RULES IN APRIORI AND FP-GROWTH ALGORITHMS : MARKET BASKET ANALYSIS TO DISCOVERRULES OF ITEM COMBINATIONS. 2(8), 1229–1248. https://doi.org/10.58344/jws.v2i8.403
Fp-growth, C. M. A. (2025). Jurnal Comasie. 01. https://doi.org/10.33884/comasiejournal.v13i1.10267
Ghous, H., & Malik, M. H. (n.d.). Deep Learning-Based Market Basket Analysis Using Association Rules. 6(1). https://doi.org/10.51153/kjcis.v6i2.166
Idris, A. I., Sampetoding, E. A. M., Yoga, V., Ardhana, P., & Maritsa, I. (2022). Comparison of Apriori , Apriori-TID and FP-Growth Algorithms in Market Basket Analysis at Grocery Stores. 6(2), 107–112. https://doi.org/10.30865/ijics.v6i2.4535
Jang, H., Yang, Y., & Park, J. S. (2021). FP-Growth Algorithm for Discovering Region-Based Association Rule in the IoT Environment. https://doi.org/10.3390/electronics10243091
Kannout, E., & Grzegorowski, M. (n.d.). Towards Addressing Item Cold-Start Problem in Collaborative Filtering by Embedding Agglomerative Clustering and FP-Growth into the Recommendation. 20(4), 1343–1366. https://doi.org/10.2298/CSIS221116052K
Ningsih, W. S., & Haryanto, E. (2022). Application of rapidminer for clustering aids cases by province using data mining k-means clustering. 5(September 2014), 89–98. https://doi.org/10.35335/idss.v5i3.101
Pratama, I. W. P. (2024). Exploring the Depths of Market Basket Analysis : A Comprehensive Guide to Transaction Analysis with FP-Growth and Apriori Algorithms. 23(2), 109–118. https://doi.org/10.24036/invotek.v23i2.1094
Prayitno, J., Saputra, B., & Rahayu, S. A. (2023). Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns. 4(1), 38–49. https://doi.org/10.47738/jads.v4i1.83
Putri, I. D., & Hardianto, R. (2024). Application of the FP-Growth Algorithm in Consumer Purchasing Pattern Analysis. 10, 2–7. https://doi.org/10.35134/jcsitech.v10i2.99
Smith, J. M. (2024). An Efficient Parallel FP-Growth Algorithm for Big Data Association Rule Mining. 4(1), 1–8. https://doi.org/10.5281/jcssa.v4i1.57
Wang, H. (2025). Consumer Behavior Analysis and Enterprise Marketing Strategy Optimization Based on Decision Tree Model and Association Rule Algorithm. 49, 101–114. https://doi.org/10.31449/inf.v49i7.7207
Widjaja, A. E. (2024). Analysis of Apriori and FP-Growth Algorithms for Market Basket Insights : A Case Study of The Bread Basket Bakery Sales. 1(1), 63–83. https://doi.org/10.47738/jdmdc.v1i1.2