Analysis of the Relationship between Products in Consumer Shopping Patterns with the Apriori Algorithm
DOI:
https://doi.org/10.52630/jmbv.v14.i01.105Keywords:
Data Mining , Apriori ALgorithm , Consumer Spending PatternsAbstract
The fitri hijab shop is one of the shops that sells hijab, in this shop there are many transactions that can be utilized and can be managed to produce information. Analysis of transactions in this shop can help shop owners to create a business strategy, such as knowing items that are often purchased together. Data mining is a field of several scientific fields that combines techniques from machine learning, pattern recognition, statistics, databases and visualization to identify problems of retrieving information from large databases. One of the algorithms from data mining techniques that can be used to find consumer shopping patterns is the apriori algorithm. The apriori algorithm is one of the algorithms in data mining that is used to retrieve data with associative rules in determining the relationship of a combination of items. From the data analysis using the python programming language, 2 association rules were obtained, namely: If you buy an instant hijab, you will buy a square hijab with a confidence value of 0.53 and if you buy a square hijab, you will buy an instant hijab with a confidence value of 0.57.
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Copyright (c) 2025 Afriosa Syawitri, Siti Rahmi Hidayatullah, Rusy Dina (Author)
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