PENDEKATAN ALGORITMA CENTROID-BASED CLUSTERING DAN FREQUENT PATTERN GROWTH (FP-GROWTH) DALAM MELAKUKAN ANALISIS POLA PEMBELIAN KONSUMEN PADA SWALAYAN

Dedek Fannyka Ikmah, NIM.: 21106060027 (2025) PENDEKATAN ALGORITMA CENTROID-BASED CLUSTERING DAN FREQUENT PATTERN GROWTH (FP-GROWTH) DALAM MELAKUKAN ANALISIS POLA PEMBELIAN KONSUMEN PADA SWALAYAN. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

In the competitive retail world, marketing is an important component that drives consumer engagement and business growth. A well-executed marketing or sales strategy is highly dependent on consumer understanding, consumer needs, and purchasing behavior. This competition is also being felt by the supermarkets in the study, so that adjustments are needed in developing their businesses to remain competitive and attract consumers. Another problem is that supermarket managers still have difficulty in making decisions related to planning sales strategies and marketing their products. This problem has an impact on declining sales results from July 2024 to January 2025. This study aims to analyze consumer purchasing patterns that occur in supermarkets. The data used is sales transaction data in February, using a combination of methods, namely Centroid-Based Clustering with FP-Growth. From this study, the best cluster was produced in the K-Medoids algorithm with a number of clusters of 2 which produced a DBI value of 1.311, then 41 association rules were obtained from modeling using the FP-Growth method. From the results used to support product sales strategy recommendations, namely product bundling with price discounts, 6 product category bundling packages were obtained, including instant food with staples, sachet drinks with staples, kitchen spices with staples, non-sachet drinks with staples, [snacks, jams, & honey] with staples, and personal care with household tools & needs. Other recommendations are membership cards and product inventory management.

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