Implementation of Data Mining to Analyze Consumer Purchasing Patterns at CV XYZ Using the Apriori Algorithm

CV XYZ is a retail store located on Jl. Tidar, Surabaya, East Java, specializing in the trade of industrial and household chemical products. To remain competitive amid rapid technological advancements and increasing competition in the area, CV XYZ has adopted online sales through the Shopee platform. This study aims to analyze consumer purchase patterns using the Apriori algorithm based on sales transaction data to support effective and efficient marketing strategies. Based on the analysis, five purchasing patterns were identified: (1) if Silicon Oil is purchased, Counterdust will also be purchased with a support value of 0.391 and a confidence value of 0.818; (2) if Cocamidopropyl Betain is purchased, Counterdust will also be purchased with a support value of 0.391 and a confidence value of 0.857; (3) if Car Shampoo is purchased, Counterdust will also be purchased with a support value of 0.359 and a confidence value of 0.868; (4) if Talc is purchased, Counterdust will also be purchased with a support value of 0.348 and a confidence value of 0.842; and (5) if Linear Alkylbenzene Sulfonate is purchased, Counterdust will also be purchased with a support value of 0.359 and a confidence value of 0.892. These findings indicate that data mining techniques using the Apriori algorithm provide an effective approach for identifying consumer purchasing patterns of chemical products sold online through the Shopee platform. This insight can help businesses optimize their marketing strategies and decision-making processes.

Authors

Publication Details

Journal
Indonesian Journal of Computer Science
Published
2025-03-06
DOI
https://doi.org/10.33022/ijcs.v14i1.4652
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

Implementation of Data Mining to Analyze Consumer Purchasing Patterns at CV XYZ Using the Apriori Algorithm

Dwi Sukma Donoriyanto, Arief Wibowo
Indonesian Journal of Computer Science
Customer churn and segmentation
article

Implementation of Data Mining to Analyze Consumer Purchasing Patterns at CV XYZ Using the Apriori Algorithm

Dwi Sukma Donoriyanto, Arief Wibowo
article en

Abstract

CV XYZ is a retail store located on Jl. Tidar, Surabaya, East Java, specializing in the trade of industrial and household chemical products. To remain competitive amid rapid technological advancements and increasing competition in the area, CV XYZ has adopted online sales through the Shopee platform. This study aims to analyze consumer purchase patterns using the Apriori algorithm based on sales transaction data to support effective and efficient marketing strategies. Based on the analysis, five purchasing patterns were identified: (1) if Silicon Oil is purchased, Counterdust will also be purchased with a support value of 0.391 and a confidence value of 0.818; (2) if Cocamidopropyl Betain is purchased, Counterdust will also be purchased with a support value of 0.391 and a confidence value of 0.857; (3) if Car Shampoo is purchased, Counterdust will also be purchased with a support value of 0.359 and a confidence value of 0.868; (4) if Talc is purchased, Counterdust will also be purchased with a support value of 0.348 and a confidence value of 0.842; and (5) if Linear Alkylbenzene Sulfonate is purchased, Counterdust will also be purchased with a support value of 0.359 and a confidence value of 0.892. These findings indicate that data mining techniques using the Apriori algorithm provide an effective approach for identifying consumer purchasing patterns of chemical products sold online through the Shopee platform. This insight can help businesses optimize their marketing strategies and decision-making processes.

Indonesian Journal of Computer ScienceVol. 14(1)
Openalex Percentile: Top 90%
Customer churn and segmentation
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