Application of Data Mining for Product Purchase Pattern Analysis with Frequent Pattern Growth (FP-Growth) Algorithm on Sales Transaction Data

Authors

  • Nuke L Chusna Lecture of Universitas Krisnadwipayana, Indonesia
  • Herwanto Herwanto Lecture of Universitas Krisnadwipayana, Indonesia
  • Indah Permata Sari Student of Universitas Krisnadwipayana, Indonesia

DOI:

https://doi.org/10.33603/jste.v1i1.6034

Abstract

The rapid growth of pet products, especially in Indonesia, makes the business competition in this field more even strict. In these conditions, a good data processing technique is needed, one of them is called the data mining technique. The algorithm used in this study is FP-Growth to generate frequent itemset that will later be used in the decision-making process that can result in a choice. This study took an object of sales transaction data from a pet shop named Ciwo Pet Shop, and the transaction data is processed by using the FP-Growth algorithm. From the results of the tests, it is found that a rule that has the best confidence value is 100% with a combination of pattern products fragrant cat sand 25 liters and equilibria kitten 7.5 kg + 750 gr, It will most certainly buy Whiskas cat food from 85 gr.

References

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Published

2021-04-28

Issue

Vol. 1 No. 1 (2021): VOLUME 1 NUMBER 1 APRIL 2021

Section

Artikel

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