PURCHASE PATTERN ANALYSIS USING FP-GROWTH ALGORITHM ON SALES TRANSACTION DATA (Case Study of SP Perfume Warehouse)

TOHIR MADANI, MUHAMMAD (2023) PURCHASE PATTERN ANALYSIS USING FP-GROWTH ALGORITHM ON SALES TRANSACTION DATA (Case Study of SP Perfume Warehouse). ["eprint_fieldopt_thesis_type_tugasakhir" not defined] thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT SP Parfum Warehouse Store serves many purchases every day, both online and offline. From the purchase data, it produces a lot of data in the form of sales data which is only seen without any follow-up for the future. Observing this, a system is needed that can determine decisions in compiling a sales strategy, namely by utilizing data mining using the association rule method to analyze patterns of consumer tendencies to buy goods simultaneously on sales transaction data. In searching for association rule patterns, the algorithm used is Frequent Pattern Growth (FP-Growth) where the algorithm can determine the data that appears most often (frequent itemset) in a data set by determining the minimum support and minimum confidence values for each item. The system created in determining the association pattern uses PHP and MySQL programming as database storage media. In this study support was determined using a 40% threshold and 70% confidence. By paying attention to the relationship between support and confidence values, store owners can make decisions in determining which items require more inventory than other items and can also make decisions in providing discount packages or bundling with high confidence patterns but have little support. From the results of this study obtained 6 patterns of association. Keywords: SP Perfume Warehouse, Data mining, Association Rules, FP-Growth

Item Type: Thesis (["eprint_fieldopt_thesis_type_tugasakhir" not defined])
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 30 May 2023 01:24
Last Modified: 30 May 2023 01:24
URI: http://eprints.uty.ac.id/id/eprint/13097

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