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

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Analisis Pola Penjualan Produk Ritel Menggunakan Algoritma Apriori di Toko Reika Zulfa Ummu Hani; 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-.17.1.2025.71-92

Abstract

This research aims to analyze product purchasing patterns at Toko Reika by utilizing the Apriori algorithm as a data mining method. The analysis process is conducted through a series of stages in Knowledge Discovery in Database (KDD), which includes data selection, cleaning, transformation, analysis, and evaluation. The results of this study successfully identified 36 association rules from the analyzed transactions, illustrating various combinations of related products. One of the most striking findings is the rule with the highest lift value, which is the combination of Basic Needs, Food Supplements, and Food Ingredients, with a lift value of 8.7. This indicates that these three products have a very strong correlation in consumer transactions. Additionally, the combination of Snacks, Basic Needs, and Food Ingredients also stands out, with a confidence value reaching 76%. This suggests that consumers who purchase one product from this combination are highly likely to purchase the other products as well. The analysis also reveals significant purchasing patterns within certain categories, such as Skincare, Food Supplements, and Bathing Supplies, which show high lift values and meaningful relationships between products in a single transaction. The insights gained from this research can be utilized to design data-driven marketing strategies, such as bundling promotions, product arrangement, and more effective stock management. It is hoped that these findings can help retail stores improve operational efficiency, maximize sales, and provide a better shopping experience for consumers.
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 Wini Audiana