Penerapan Algoritma Apriori Dalam Menentukan Pola Pergerakan Kebutuhan Distribusi Pada PT. Satria Teknik Indonesia

Rama Yoviyardi; April  Lia Hananto; Nurapriani Nurapriani; Huda  Huda

doi:10.33998/processor.2025.20.1.2207

Authors

Rama Yoviyardi Universitas Buana Perjuangan Karawang
April Lia Hananto Universitas Buana Perjuangan
Nurapriani Nurapriani Universitas Buana Perjuangan
Huda Huda Universitas Buana Perjuangan

DOI:

https://doi.org/10.33998/processor.2025.20.1.2207

Keywords:

Apriori algorithm, Associattion Rules, Distribution, Inventory management

Abstract

In an increasingly competitive business environment, companies are required to make more precise strategic decisions to enhance operational efficiency. The shift in customer demand trends has become a major challenge faced by PT Satria Teknik Indonesia, a goods distribution company. To address this challenge, the company can leverage transaction data to analyze customer purchasing patterns. By utilizing the results of this analysis, PT Satria Teknik Indonesia can improve the accuracy of customer demand predictions, accelerate data-driven decision-making, and optimize inventory management. One effective method for this analysis is the Apriori algorithm. The data used were obtained from the company's transaction recording system during the period from January 2023 to October 2024 and were analyzed to discover association rules in large datasets and identify relationships between products that are frequently purchased together. The results of this study reveal two items that are prioritized for ordering: Back Support and Safety Shoes Cheetah. If customers purchase Back Support, they are highly likely to also purchase Safety Shoes Cheetah, with a support value of 20.22% and a confidence level of 100%. Conversely, if customers purchase Safety Shoes Cheetah, they tend to also buy Back Support, with a support value of 20% and a confidence level of 94.74%. This study identifies a strong purchasing association pattern between Back Support products and Safety Shoes Cheetah, providing empirical evidence of the benefits of implementing data mining techniques to improve inventory management effectiveness and better respond to customer needs

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