IMPLEMENTATION OF DATA MINING TO DETERMINE SALES PATTERNS USING THE APRIORI METHOD

MUHAMMAD ZAKUAN RITONGA, NPM 2009100034 (2024) IMPLEMENTATION OF DATA MINING TO DETERMINE SALES PATTERNS USING THE APRIORI METHOD. Tugas_Akhir (Artikel) Sinkron : Jurnal dan Penelitian Teknik Informatika, 8 (2). pp. 1100-1106. ISSN 2541-2019 (e-ISSN) / 2541-044X (p-ISSN)

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Abstract

Research on the Implementation of Data Mining to Determine Sales Patterns Using the Apriori Method is an effort to understand and utilize sales data in making more informed and strategic business decisions. The main goal of this research is to extract hidden patterns from large sales data sets, which cannot be discovered by manual analysis alone. This research process is divided into several key stages, namely Data Selection, Preprocessing, Transformation, and Data Mining. The research results show that the Apriori method is effective in finding purchasing patterns. In terms of the frequency of 2 itemsets, the highest support value was found to be 1, which indicates that the combination of the two products is always purchased together in all transactions. For 3 itemsets and 4 itemsets, the high support value of 0.9 also indicates the existence of product combinations that are often purchased together. In terms of confidence, 2 itemsets show the highest value of 1.25, indicating that purchasing one product has a high tendency to be followed by purchasing other products. For 3 itemsets and 4 itemsets, the confidence values show a slightly lower trend but are still significant. Furthermore, lift analysis provides additional insight into the strength of association between itemsets, with 4 itemsets showing the highest lift value of 1.30, indicating the product combination has a very strong association compared to random expectations. This research confirms the potential of the Apriori method in finding valuable sales patterns, which can help companies make strategic decisions for increasing sales and customer satisfaction. Keywords : Association; Apriori; Data Mining; Frequency; Sale

Item Type:	Article
Uncontrolled Keywords:	Association; Apriori; Data Mining; Frequency; Sale
Subjects:	T Technology > T Technology (General) T Technology > TN Mining engineering. Metallurgy Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	31 May 2024 08:09
Last Modified:	31 May 2024 08:09
URI:	http://repository.ulb.ac.id/id/eprint/707

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