Product Stock Supply Analysis System with FP Growth Algorithm

Authors

  • Dwi Hartanti Universitas Duta Bangsa Surakarta, Indonesia
  • Vihi Atina Universitas Duta Bangsa Surakarta, Indonesia
Pages Icon

DOI:

https://doi.org/10.51519/journalisi.v5i4.580

Keywords:

Association Rule, Extreme Programming, FP-Growth, Supply Analysis

Abstract

This study explores the application of Data Mining in deciphering consumer purchasing patterns at Tani Heritage Shop, a retailer specializing in agricultural products. Facing the challenge of managing a high volume of daily sales transactions, the shop often encounters difficulties in tracking which products are frequently purchased together. This lack of insight leads to a critical issue: popular products running out of stock unexpectedly. To address this, the research focuses on developing a product stock supply analysis system, utilizing the FP Growth Algorithm. The FP Growth Algorithm, a powerful tool in Data Mining, is employed to analyze sales transaction data and identify consumer purchasing trends, particularly products bought simultaneously. This approach is designed to provide insights into optimal stocking strategies, ensuring the availability of in-demand products. The research methodology involves applying the FP Growth Algorithm to model the product stock supply system, using specific sales data attributes. The results of this study are significant. By setting parameters such as a minimum support value of 30%, a confidence value of 70%, and targeting the highest lift ratio value of 3.67, the research successfully derives several key association rules from the FP Growth algorithm. These rules are instrumental in optimizing the product stock supply analysis system.

Downloads

Download data is not yet available.

References

B. R. Sukarno, “Implementing business development strategies with business models canvas,” Manova J., vol. IV, pp. 51–61, 2021, doi: 10.15642/manova.v4i2.456.

S. A. Rahayu, “Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns,” J. Appl. Data Sci., vol. 4, no. 1, pp. 38–49, Jan. 2023, doi: 10.47738/jads.v4i1.83.

A. Saxena and V. Rajpoot, “A Comparative Analysis of Association Rule Mining Algorithms,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1099, no. 1, p. 12032, 2021, doi: 10.1088/1757-899x/1099/1/012032.

Y. Lin, F. Lin, D. Huang, and X. Fang, “Voltage sag severity analysis based on improved FP-Growth algorithm and AHP algorithm,” J. Phys. Conf. Ser., vol. 1732, no. 1, 2021, doi: 10.1088/1742-6596/1732/1/012088.

W. P. Nurmayanti et al., “Market Basket Analysis with Apriori Algorithm and Frequent Pattern Growth (Fp-Growth) on Outdoor Product Sales Data,” Int. J. Educ. Res. Soc. Sci., vol. 2, no. 1, pp. 132–139, 2021, doi: 10.51601/ijersc.v2i1.45.

S. Herdyansyah, E. H. Hermaliani, L. Kurniawati, and S. R. Sri Rahayu, “Analysis of the Association Rule Method uses the FP-Growth algorithm against sales data (Study Case of Blessing Store),” J. Khatulistiwa Informatics, vol. 8, no. 2, pp. 127–133, 2020, doi: 10.31294/jki.v8i2.9277.

L. Zahrotun, A. Hendri, S. Jones, R. Selatan, and K. Uad, “Fp-Growth Algorithm For Searching Book Borrowing Transaction Patterns And Study Program Suitability,” Int. J. Inf. Syst. Technol., vol. 5, no. 158, pp. 564–569, 2022, doi: 10.30645/ijistech.v5i5.180.

A. Anas, “Implementation of a priori algorithm to get the pattern of the thesis supervisor STIE-GK Muara Bulian,” Sci. J. media sisfo, vol. 15, no. 1, pp. 19–27, 2021, doi: 10.33998/mediasisfo.2021.15.1.972.

N. Isa, S. K. Neddy, and N. Mohamed, “Association rule mining using fp-growth algorithm to prevent maverick buying,” ISCAIE 2021 - IEEE 11th Symp. Comput. Appl. Ind. Electron., pp. 77–81, 2021, doi: 10.1109/ISCAIE51753.2021.9431821.

D. Melati and T. S. Wahyuni, “Association Rule In determining the cross-selling of the product using the FP-Growth algorithm,” Votetechnics (Vocational Electron. Informatics Eng., vol. 7, no. 4, p. 102, 2020, doi: 10.24036/voteteknika.v7i4.106499.

A. Wadanur and A. A. Sari, “Implementation of Apriori and FP-Growth Algorithms in Spare Parts Sales,” Edumatic J. Inf. Educ., vol. 6, no. 1, pp. 107–115, 2022, doi: 10.29408/edumatic.v6i1.5470.

L. N. Rani, S. Defit, and L. J. Muhammad, “Determination of Student Subjects in Higher Education Using Hybrid Data Mining Method with the K-Means Algorithm and FP Growth,” Int. J. Artif. Intell. Res., vol. 5, no. 1, pp. 91–101, 2021, doi: 10.29099/ijair.v5i1.223.

H. Yulianti and G. T. Pranoto, “The Design of a Monitoring Application System for The Production of Foam Products Using the UML And Waterfall Methods,” JISA (Journal Informatics Sci., vol. 4, no. 2, pp. 164–172, 2021, doi: 10.31326/jisa.v4i2.1045.

Downloads

Published

2023-12-02

Issue

Vol. 5 No. 4 (2023): Journal of Information Systems and Informatics

Section

Articles

License

Authors Declaration

  1. The Authors certify that they have read, understood, and agreed to the Journal of Information Systems and Informatics (JournalISI) submission guidelines, policies, and submission declaration. The submission has been prepared using the provided template.
  2. The Authors certify that all authors have approved the publication of this manuscript and that there is no conflict of interest.
  3. The Authors confirm that the manuscript is their original work, has not received prior publication, is not under consideration for publication elsewhere, and has not been previously published.
  4. The Authors confirm that all authors listed on the title page have contributed significantly to the work, have read the manuscript, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission.
  5. The Authors confirm that the manuscript is not copied from or plagiarized from any other published work.
  6. The Authors declare that the manuscript will not be submitted for publication in any other journal or magazine until a decision is made by the journal editors.
  7. If the manuscript is finally accepted for publication, the Authors confirm that they will either proceed with publication immediately or withdraw the manuscript in accordance with the journal’s withdrawal policies.
  8. The Authors agree that, upon publication of the manuscript in this journal, they transfer copyright or assign exclusive rights to the publisher, including commercial rights

How to Cite

[1]
D. Hartanti and V. Atina, “Product Stock Supply Analysis System with FP Growth Algorithm”, journalisi, vol. 5, no. 4, pp. 1312–1320, Dec. 2023, doi: 10.51519/journalisi.v5i4.580.

Most read articles by the same author(s)