Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Apriori pada ABC Baby Shop
DOI:
https://doi.org/10.36050/k58xep72Keywords:
Algoritma Apriori, Aturan Asosiasi, Bundling Product, CRISP-DM, Data MiningAbstract
ABC Baby Shop is a store that sells baby, mother, and child supplies. Based on the results of interviews with the owner of ABC Baby Shop, it is known that the store's current product bundling offers are arranged based on stock and estimates from the store. Meanwhile, based on transaction data from February 2024 to January 2025, it is known that no product bundling has been sold. This indicates that the current product bundling is still ineffective in attracting customer buying interest. Therefore, it is necessary to analyze customer purchasing patterns by applying the Apriori algorithm, which can then be used as a guide in compiling product bundling to improve service and sales. The methodology used in this study is CRISP-DM, which has six stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. Meanwhile, the programming language used is Python with Google Colab tools. The results are the combination of Mo Ma Mi Bubbly Body and Bee Me Nourishing Balm products with Moell Sunscreen products has a confidence value of 51.06% with a lift of 3.5. The results of this analysis are then presented visually through a dashboard developed using the RAD methodology, the PHP programming language, and a MySQL database, to make it easier for users to understand and utilize the resulting information. The findings from this analysis can be used by stores to inform data-driven decision-making.
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Copyright (c) 2026 Chintya Lyra Hartanto, Desi Pibriana (Author)
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