CD Skripsi
Menentukan Pola Penjualan Sparepart Menggunakan Metode Algoritma Apriori (Studi Kasus: Toko Bintang Jaya)
This study aims to analyze the sales patterns of spare parts at Toko Bintang Jaya, Pekanbaru, by applying the Apriori algorithm. In the era of intense business competition, understanding sales patterns is crucial for retail stores to optimize their sales strategies. Using sales data from January to June 2023, this research identifies spare parts that are frequently purchased together by customers. The analysis was conducted through several stages, including data preparation, data transformation, and the formation of frequent itemsets based on minimum support values. The results show that the Apriori algorithm, implemented using the R programming language on the sales data, produced 6 association rules with lift ratios greater than 1, indicating strong relationships between items. These findings predict spare parts that are often purchased together, providing strategic insights for inventory management, product arrangement, and more effective promotions.
Keywords: Apriori Algorithm, Data Mining, Sales Patterns, Spare Parts.
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