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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) CSRID
Wini Audiana
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Application Of Market Basket Analysis For Sales Transaction Analysis Using Association FP-Growth Algorithm Wini Audiana; Tahyudin, Imam
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.33-49

Abstract

In an increasingly competitive business world, leveraging transaction data has become crucial for understanding consumer behavior and designing effective marketing strategies. This study aims to apply the FP-Growth algorithm in Market Basket Analysis (MBA) to identify consumer purchase patterns at KS Swalayan. The data analyzed in this research was taken from sales transactions that occurred during October 2024, with key attributes including product codes, product names, quantity, unit price, total price, and discounts. This research follows the Knowledge Discovery in Databases (KDD) framework, which includes stages of data selection, data cleaning, transformation, pattern collection, and result evaluation. The research findings indicate that the FP-Growth algorithm successfully identified significant associative relationships between various products. For example, there is a relationship between the products "Snack and Roti" and "Susu," which shows a lift value of 1.414861701, indicating a strong correlation between them. These findings provide the basis for marketing strategy recommendations such as product bundling, optimizing shelf layouts, and more efficient stock management. Additionally, the results of this study have the potential to improve consumer shopping experiences by offering products that are frequently bought together. Overall, this study highlights the effectiveness of the FP-Growth algorithm in uncovering consumer purchase patterns, which can support data-driven decision-making and improve marketing strategy efficiency in the retail sector. The implementation of this technique can serve as a valuable tool for store managers to enhance their competitiveness and business performance.
Penerapan Algoritma FP-Growth untuk Strategi Penjualan Toko Kelontong Cipta Lestari Tarwoto; Ahnaf Vanning AL-Haq; Anindya Fidela; Wini Audiana; Zulfa Ummu Hani
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3278

Abstract

This research uses the FP-Growth algorithm to identify sales patterns at the Cipta Lestari convenience store to support inventory management efficiency and marketing strategies. The data used in this research consists of daily sales transaction data that includes product types and the quantities sold. This analysis employs a support parameter of 0.95 and a confidence level of 0.8, with a maximum limit of 100,000 items. The results indicate that products such as Kchoco, sambal sauce, and tea 3350ml are often purchased together with Torabika coffee, soy sauce, and instant fried noodles. This combination pattern enables the store to create more effective product promotions and optimize inventory. The goal of this research is to develop business strategies that are more responsive to customer needs, enhance satisfaction with the right product offerings, and strengthen competitive marketing. This research is expected to contribute to the development of traditional marketing strategies and serve as a reference for analyzing consumer purchasing patterns in future studies.
Co-Authors Ahnaf Vanning AL-Haq Anindya Fidela Imam Tahyudin Tarwoto Zulfa Ummu Hani