Marketing Strategy Using Frequent Pattern Growth

Nazori Suhandi; Rendra Gustriansyah

doi:10.47709/cnahpc.v3i2.1039

Authors

Nazori Suhandi Universitas Indo Global Mandiri
Rendra Gustriansyah Universitas Indo Global Mandiri

DOI:

10.47709/cnahpc.v3i2.1039

Keywords:

Association Rules, Data mining, FP-Growth, Marketing Strategy, Printing

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Abstract

The biggest problem faced by printing companies during the Covid-19 pandemic was that the number of orders was unstable and tends to decrease, which had the potential to harm the company. Therefore, various appropriate marketing strategies were needed so that the number of product orders was relatively stable and even increases. The impact was that the company could survive and continued to grow. This study aimed to assist company managers in developing appropriate marketing strategies based on association rules generated from one of the data mining methods, namely the Frequent Pattern Growth (FP-Growth) method. The case study of this research was a printing company where there was no similar research that used a printing company's dataset. This study produced nine association rules that meet a minimum of 25% support and a minimum of 60% confidence, but only two association rules that had a high positive correlation, namely for a custom paper bag and banner products. Therefore, several marketing strategies were suggested that could be used as guidelines for companies in managing sales packages and giving special discounts on a product. The results of this study are expected to trigger an increase in the number of product orders because this study tried to find the right product for consumers and did not try to find the right consumers for a product.

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