Using the Apriori Algorithm to Identify  Purchase Patterns for Enhancing Sales in Personal  Shopper Services

Euis Fadilah; Ahmad Faqih; Sandy Eka Permana

doi:10.59934/jaiea.v4i2.741

Authors

Euis Fadilah Informatics Engineering, STMIK IKMI Cirebon
Ahmad Faqih Informatics Engineering, STMIK IKMI Cirebon
Sandy Eka Permana Informatics Management, STMIK IKMI Cirebon

DOI:

https://doi.org/10.59934/jaiea.v4i2.741

Keywords:

Apriori Algorithm, Purchasing Patterns, Delivery Service, Data Mining, Marketing Strategy.

Abstract

This research aims to explore the application of the Apriori algorithm in identifying purchasing patterns in the drop-off service industry in order to increase sales. Drop-off services often face challenges in designing effective marketing strategies due to limited understanding of customer purchasing behavior. In this study, the Apriori algorithm is applied to uncover recurring purchase patterns among customers, which are then used to develop more efficient marketing strategies. Customer transaction data is analyzed to find associations that reflect their purchasing preferences. The results show that the application of the Apriori algorithm successfully identifies patterns that can improve marketing strategies and, ultimately, increase sales. This research emphasizes the importance of applying data mining techniques to improve the performance of delivery services.

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