Analysis of Customer Transaction Data Associations Based on The Apriori Algorithm

Dublin Core

Title

Analysis of Customer Transaction Data Associations Based on The Apriori Algorithm

Subject

Data Mining; Association Rules; Apriori Algorithm; Minimal Support; Confidence.

Description

UD Dian Pertiwi is one of the small and medium enterprises engaged in materials with the main product is building materials. This business experiences large amounts of transactions every day, the data obtained becomes increasingly large, and it will only be limited to a pile of useless data or commonly called junk. By utilizing a data mining approach apriori algorithm technique, the data can be utilized to support the sales process and achieve a target of UD Dian Pertiwi. Based on research and data mining that has been done using association analysis and apriori algorithms by applying a minimum of support = 1% and a minimum of confidence = 70% resulted in the ten strongest association rules can be used by UD Dian Pertiwi in the process of applying a sales strategy including determining interrelationships, in short, the product has the potential to be purchased at the same time, increasing the amount of product stock and conducting promotions.

Creator

Tri Astuti a,*, Bella Puspita

Date

2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Citation

Tri Astuti a,*, Bella Puspita, “Analysis of Customer Transaction Data Associations Based on The Apriori Algorithm,” Repository Horizon University Indonesia, accessed June 6, 2025, https://repository.horizon.ac.id/items/show/9209.