Market Basket Analysis using the Frequent Pattern Growth Algorithm at RJ Mart Melaris

ubay hakim arrafiq; Yufis Azhar; Galih Wasis Wicaksono

doi:10.32520/stmsi.v13i4.3634

Market Basket Analysis using the Frequent Pattern Growth Algorithm at RJ Mart Melaris

ubay hakim arrafiq, Yufis Azhar, Galih Wasis Wicaksono

Abstract

Marketing strategy in a business is a major factor in the success or failure of a business both micro, medium and macro. With an effective and efficient marketing strategy It is hoped that it can increase income to the maximum. Currently, technological developments are very fast, including carrying out transactions that are directly connected to the database, resulting in very large data growth. The data itself can be used as a source of information to determine the right marketing strategy. The main aim of this research is to maximize the existing marketing strategy at RJ Mart Melaris by utilizing data as a source of information and consideration. The choice of Market Basket Analysis as a method for utilizing data is because these medium-sized businesses need consideration to develop sales by forming effective product packages. Frequent Pattern Growth is used as an effective algorithm to form combinations of product items or what is usually called an association rule. Some of the benefits resulting from this research are knowing how likely a product is to be purchased at the same time as other products, what products are sold the most and the least so that you can maximize stock of goods, and the relationship between products to maximize the placement of goods. This research produced 8 Association Rules or product combinations with 6 different items. The strongest rule that is generated is that if you buy special fried Indomie and chicken curry Indomie, you will definitely also buy special chicken Indomie with an association strength of 8,472. Meanwhile, the item that is most often purchased together with other items is the special fried Indomie, which sells 50% together with the special chicken curry Indomie and special chicken Indomie. Apart from that, this research also produced 2 different groups of items, each item in the group has a sales relationship.

Full Text:

PDF

References

I. P. Azhari, A. S. Wahyuni, P. Rahmadani, O. Delisha, and U. M. Riau, “INTRODUCING STRATEGIC MANAGEMENT TO GROCERY STORE KEDAI BU NUR FOR COMPETE WITH MODERN RETAIL KEDAI BU NUR GUNA MENGHADAPI PERSAINGAN RITEL MODERN,” vol. 3, no. 3, pp. 406–411, 2023.

Sutanty Marisa, Asmini, Karmeli Elly, Suprianto, and Sucihati Roos Nana, “2324-Article Text-6025-1-10-20221208,” vol. 11, no. 2, 2022.

S. A. Arnomo, “Market Basket Analysis pada Barang Minimarket dimasa Pandemi Covid-19,” J. Sist. dan Teknol. Inf., vol. 9, no. 2, p. 127, 2021, doi: 10.26418/justin.v9i2.43243.

N. Ramadhani, A. W. Syahroni, A. Supikar, and W. Zumam, “Penerapan Market Basket Analysis Menggunakan Metode Multilevel Association Rules dan Algoritma ML_T2L1 Pada Data Order PT. Unirama,” Insa. Comtech Inf. Sci. Comput. Technol. J., vol. 7, no. 1, 2022, doi: 10.53712/jic.v7i1.1674.

A. H. Nasyuha et al., “Frequent pattern growth algorithm for maximizing display items,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 19, no. 2, pp. 390–396, 2021, doi: 10.12928/TELKOMNIKA.v19i2.16192.

D. A. Silitonga and A. P. Windarto, “Implementasi Market Basket Analysis Menggunakan Assocation Rule Menerapkan Algoritma FP-Growth,” J. Inf. Syst. Res., vol. 3, no. 2, pp. 101–109, 2022, doi: 10.47065/josh.v3i2.1239.

P. H. Lu, J. L. Keng, K. L. Kuo, Y. F. Wang, Y. C. Tai, and C. Y. Kuo, “An apriori algorithmbased association rule analysis to identify herb combinations for treating uremic pruritus using Chinese herbal bath therapy,” Evidence-based Complement. Altern. Med., vol. 2020, 2020, doi: 10.1155/2020/8854772.

M. Syahru Romadhon and A. Kodar, “Implementasi Metode Market Basket Analysis (Mba) Menggunakan Algoritma Apriori Dalam Transaksi Penjualan (Studi Kasus: Kafe Ruang Temu),” J. SAINTEKOM, vol. 10, no. 2, p. 138, 2020, doi: 10.33020/saintekom.v10i2.137.

I. Qoniah and A. T. Priandika, “ANALISIS MARKET BASKET UNTUK MENENTUKAN ASOSSIASI RULE DENGAN ALGORITMA APRIORI (STUDI KASUS: TB. MENARA),” J. Teknol. dan Sist. Inf., vol. 1, no. 2, pp. 26–33, 2020, doi: 10.33365/jtsi.v1i2.368.

F. Firmansyah and A. Yulianto, “Market Basket Analysis for Books Sales Promotion using FP Growth Algorithm, Case Study : Gramedia Matraman Jakarta,” J. Informatics Telecommun. Eng., vol. 4, no. 2, pp. 383–392, 2021, doi: 10.31289/jite.v4i2.4539.

R. Purwaningsih, Y. Widharto, N. Susanto, and L. T. Utami, “REDESAIN TATA LETAK PRODUK DI SUPERMARKET BERDASARKAN PERILAKU PEMBELIAN DENGAN METODE MARKET BASKET ANALYSIS,” J@ti Undip J. Tek. Ind., vol. 15, no. 3, pp. 196–202, 2020, doi: 10.14710/jati.15.3.196-202.

S. Anas, N. Rumui, R. Andi Roy, and P. H. Saputro, “Comparison of Apriori Algorithm and FP-Growth in Managing Store Transaction Data,” Int. J. Comput. Inf. Syst. Peer Rev. J., vol. 03, no. 04, pp. 2745–9659, 2022, [Online]. Available: https://ijcis.net/index.php/ijcis/index

P. R. Wulandari, I. M. A. D. Suarjaya, and N. K. D. Rusjayanthi, “Komparasi Algoritma Pincer Search dan Algoritma FP- Growth pada Stok Barang di Toko X,” vol. 21, no. 2, pp. 280–291, 2022.

A. K. Siregar, B. A. Kusuma, A. P. Kuncoro, and Suliswaningsih, “Perbandingan Algoritme FP-Growthdan Eclat untuk Analisis Pola Pembelian Konsumen pada Toko ‘X,’” Sist. Inf., vol. 1, no. 3, pp. 125–128, 2018.

N. Wulandari and M. Aburizal Purnama, “Market Basket Analysis Dalam Penentuan Paket Produk Menggunakan Algoritma Fp-Growth,” Jika, vol. ISSN, no. april, pp. 57–63, 2022.

DOI: https://doi.org/10.32520/stmsi.v13i4.3634

Article Metrics

Abstract view : 189 times
PDF - 42 times

Refbacks

There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Username
Password
Remember me