Enhancing Marketing Strategies for Office Stationery Stores Using Equivalence Class Transformation Algorithms

Authors

  • Ega Silfa Yuliana Universitas Multimedia Nusantara, Indonesia
  • Raymond Oetama Multimedia Nusantara University image/svg+xml

DOI:

https://doi.org/10.33379/gtech.v8i1.3441

Keywords:

office supply business, ECLAT, Marketing strategy

Abstract

Office stationery stores facilitate operations for offices, schools, and businesses. However, the store owner must overcome the challenge of selecting the right products for promotion. This research aims to tackle this issue by comparing the performance of the Equivalence Class Transformation algorithms in discovering association rules using Support, confidence, and lift ratios. The findings reveal that the algorithm generates association rules based on Support, confidence, and lift values. Ten critical rules are identified, shedding light on algorithm effectiveness. Ultimately, this study underscores the significance of refining marketing approaches for brick-and-mortar stationery businesses and the value of data-driven methods in aiding decision-making. In the early promotion catalog phase, priority is assigned to rules with solid agreement by the Shop Owner, guiding the selection of featured items based on robust product associations.

References

Aldino, A. A., Pratiwi, E. D., Setiawansyah, Sintaro, S., & Putra, A. D. (2021). Comparison of Market Basket Analysis to Determine Consumer Purchasing Patterns Using Fp-Growth and Apriori Algorithm. 2021 International Conference on Computer Science, Information Technology, and Electrical Engineering, ICOMITEE 2021, 29–34. https://doi.org/10.1109/ICOMITEE53461.2021.9650317

Chen, A. H.-L., & Gunawan, S. (2023). Enhancing Retail Transactions: A Data-Driven Recommendation Using Modified R.F.M. Analysis and Association Rules Mining. Applied Sciences, 13(18), 10057. https://doi.org/10.3390/app131810057

Hardjadinata, H., Oetama, R. S., & Prasetiawan, I. (2021). Facial Expression Recognition Using Xception And DenseNet Architecture. 2021 6th International Conference on New Media Studies (CONMEDIA), 60–65.

Imaroh, T. S., Widiyani, K., & Muttaqien, F. (2023). Value Chain and Supply Chain Management of Products from Women Farmer Groups in South Tangerang. Wiga: Jurnal Penelitian Ilmu Ekonomi, 13(2), 190–203.

Jia, X. (2021). Research on the Role of Big Data Technology in the Reform of English Teaching in Universities. Wireless Communications and Mobile Computing, 2021, 1–13. https://doi.org/10.1155/2021/9510216

Kavitha, & Subbaiah. (2020). Association Rule Mining using Apriori Algorithm for Extracting Product Sales Patterns in Groceries. International Journal of Engineering Research and Technology (IJERT), 8(3), 5–8. www.ijert.org

Liu, M., Gao, Y., Yang, K., Xu, J., Zheng, Q., Zhao, L., Ge, L., Li, L., Zhang, J., & Tian, J. (2022). Interpretation of STROBE-MR: a statement for strengthening the reporting of observational studies in epidemiology using Mendelian randomization. Chinese Journal of Evidence-Based Medicine, 22(8), 978–987. https://doi.org/10.7507/1672-2531.202112103

Liu, X., & Shi, A. (2023). Online Bundled Pricing Strategy for Agricultural Products Considering Consumers' Organic Preferences.

Luna, J. M., Fournier-Viger, P., & Ventura, S. (2019). Frequent itemset mining: A 25 years review. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(6), e1329. https://doi.org/10.1002/widm.1329

Martins, P., Rodrigues, P., Martins, C., Barros, T., Duarte, N., Dong, R. K., Liao, Y., Comite, U., & Yue, X. (2021). Preference between individual products and bundles: effects of complementary, price, and discount level in Portugal. Journal of Risk and Financial Management, 14(5), 192.

Mohapatra, D., Tripathy, J., Mohanty, K. K., & Nayak, D. S. K. (2021). Interpretation of Optimized Hyper Parameters in Associative Rule Learning using Eclat and Apriori. Proceedings - 5th International Conference on Computing Methodologies and Communication, ICCMC 2021, 879–882. https://doi.org/10.1109/ICCMC51019.2021.9418049

Mukonza, C., & Swarts, I. (2020). The influence of green marketing strategies on business performance and corporate image in the retail sector. Business Strategy and the Environment, 29(3), 838–845. https://doi.org/10.1002/bse.2401

Paradkar, R. U. (2022). Detecting Customer Purchasing Patterns using Association Rule Mining. Dublin, National College of Ireland.

Qisman, M., Rosadi, R., & Abdullah, A. S. (2021). Market basket analysis using apriori algorithm to find consumer patterns in buying goods through transaction data (case study of Mizan computer retail stores). Journal of Physics: Conference Series, 1722(1), 12020. https://doi.org/10.1088/1742-6596/1722/1/012020

Santoso, J. T., Jumini, S., Bhawika, G. W., Susilo, D., Wibowo, D., & Rahim, R. (2021). Unsupervised Data Mining Technique for Clustering Library in Indonesia. Library Philosophy and Practice, 4866.

Somya, R., Winarko, E., & Priyanta, S. (2022). A hybrid recommender system based on customer behavior and transaction data using generalized sequential pattern algorithm. Bulletin of Electrical Engineering and Informatics, 11(6), 3422–3432.

Ünvan, Y. A. (2021). Market basket analysis with association rules. Communications in Statistics - Theory and Methods, 50(7), 1615–1628. https://doi.org/10.1080/03610926.2020.1716255

Wei, X., Wei, Y., Chen, P., Fan, C., Luo, H., Zhao, Q., & Kong, Y. (2019). The Analysis of "Online Silk Road" from the Perspective of Big Data. In The New Silk Road Leads through the Arab Peninsula: Mastering Global Business and Innovation (pp. 97–114). Emerald Publishing Limited.

Wilim, N. N., & Oetama, R. S. (2021). Sentiment Analysis About Indonesian Lawyers Club Television Program Using K-Nearest Neighbor, Naïve Bayes Classifier, And Decision Tree. IJNMT (International Journal of New Media Technology), 8(1), 50–56. https://doi.org/10.31937/ijnmt.v8i1.1965

Wu, P., Niu, X., Fournier-Viger, P., Huang, C., & Wang, B. (2022). UBP-Miner: An efficient bit based high utility itemset mining algorithm. Knowledge-Based Systems, 248, 108865. https://doi.org/10.1016/j.knosys.2022.108865

Yan, H., Yang, N., Peng, Y., & Ren, Y. (2020). Data mining in the construction industry: Present status, opportunities, and future trends. Automation in Construction, 119, 103331.

Zhang, Y., Niyato, D., Wang, P., & Han, Z. (2020). Data Services Sales Design with Mixed Bundling Strategy: A Multidimensional Adverse Selection Approach. IEEE Internet of Things Journal, 7(9), 8826–8836. https://doi.org/10.1109/JIOT.2020.2999824

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Published

2023-12-20

How to Cite

Enhancing Marketing Strategies for Office Stationery Stores Using Equivalence Class Transformation Algorithms. (2023). G-Tech: Jurnal Teknologi Terapan, 8(1), 1-9. https://doi.org/10.33379/gtech.v8i1.3441

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