CD Skripsi

Analisis Pola Pembelian Konsumen Pada Coffee Shop Terakota Menggunakan Algoritma Fp-Growth

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Suboptimal raw material inventory management and imprecise marketing strategies have become major challenges for Coffee Shop Terakota in Indragiri Hulu Regency. This study aims to analyze consumer purchase patterns to provide recommendations for products that are frequently bought together. The results of this analysis are expected to assist management in maintaining optimal raw material stock availability and in developing more effective product bundling strategies. The method used is the FP-Growth algorithm, an efficient data mining technique for discovering product association patterns from large transaction datasets. The data analyzed consisted of 2.599 sales transactions at Coffee Shop Terakota from January to February 2025. The analysis, with a minimum support threshold set at 1% (0.01) and a minimum confidence threshold of 20% (0.2), showed that the product combination of “AMERICANO HOT” and “KOPI BOTOL” has a confidence of 41.5% and a lift of 2.02, while “AMERICANO HOT” and “KOPI TERAKOTA COLD” have a confidence of 34.1% and a lift of 3.96. These patterns indicate a strong association between products that are frequently purchased together. These findings can be used to optimize raw material stock availability and design targeted product bundling strategies.
Keywords: Association Rules, Product Bundling, Data Mining, FP-Growth, Purchasing Patterns

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2103110835

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2103110835

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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