ANALISA POLA PEMBELIAN KONSUMEN MENGGUNAKAN ALGORITMA FP-GROWTH PADA NUSA RICEBOWL & BURGER

Lutfiyatul Ulfa; Syaifur Rahmatullah; Irmawati Irmawati

doi:10.52362/jisamar.v7i2.1066

Lutfiyatul Ulfa Universitas Nusa Mandiri
Syaifur Rahmatullah Universitas Bina Sarana Informatika
Irmawati Irmawati Universitas Bina Sarana Informatika

DOI: https://doi.org/10.52362/jisamar.v7i2.1066

Abstract

Currently, competition in the trading business world is very tight, especially in the fast food restaurant industry, such as Nusa Ricebowl & Burger, to attract customer interest in the food products being sold. So a strategy is needed to beat the market, especially in product sales at Nusa Ricebowl & Burger. With the right strategy, it will sell products quickly so that sales can increase to achieve maximum profit so that maximum profit is achieved which is the company's goal. By using Nusa Ricebowl & Burger transaction data, you can find out what products consumers buy the most and can also determine consumer buying patterns. The amount of sales transaction data available, of course, makes it more difficult to analyze data manually, so it must be done with the help of a system so that sales patterns are easily obtained. One common method used to analyze consumer buying patterns is basket analysis or market basket analysis (MBA). The research applies the FP-Growth algorithm in carrying out the data mining process to find consumer purchasing patterns at Nusa Ricebowl & Burger Stores. To find the frequency between items with a support value of 20% and 30% confidence. This is done by looking for a single path that is combined with the Conditional FP-Tree that has been obtained. The overall results obtained from the sales sample data are 22 rules consisting of 2 association rules that meet 20% support and 2 rules that meet 30% confidence. Of the 110 association rule transaction data that met the requirements ≥ 0.30 were: P→H 0.40 (if the consumer buys Aqua, then he buys Nusa Dua) it can be concluded that the Nusa Dua and Aqua menus are the most frequently purchased by consumers together. The rules have generated new information about consumer buying patterns that are not yet known. This can be used to help shop owners maintain good quality for consumers.

Downloads

Download data is not yet available.

References

[1] M. Syahril, K. Erwansyah, and M. Yetri, “Penerapan Data Mining Untuk Menentukan Pola Penjualan Peralatan Sekolah Pada Brand Wigglo Dengan Menggunakan Algoritma Apriori,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 3, no. 1, p. 118, 2020.
[2] H. Santoso, I. P. Hariyadi, and Prayitno, “Data Mining Analisa Pola Pembelian Produk,” Tek. Inform., no. 1, pp. 19–24, 2016.
[3] F. Elfaladonna and A. Rahmadani, “Analisa Metode Classification-Decission Tree Dan Algoritma C.45 Untuk Memprediksi Penyakit Diabetes Dengan Menggunakan Aplikasi Rapid Miner,” SINTECH (Science Inf. Technol. J., vol. 2, no. 1, pp. 10–17, 2019.
[4] A. Maulana and A. A. Fajrin, “Penerapan Data Mining Untuk Analisis Pola Pembelian Konsumen Dengan Algoritma Fp-Growth Pada Data Transaksi Penjualan Spare Part Motor,” Klik - Kumpul. J. Ilmu Komput., vol. 5, no. 1, p. 27, 2018.
[5] H. Herasmus, “Analisa Customer Service System Menggunakan Metode Data Mining Dengan Algoritma Fp-Growth (Studi Kasus Di Pt Batamindo Investment Cakrawala),” J. Tek. Ibnu Sina, vol. 2, no. 2, pp. 37–49, 2017.
[6] S. Suhada, D. Ratag, G. Gunawan, D. Wintana, and T. Hidayatulloh, “Penerapan Algoritma Fp-Growth Untuk Menentukan Pola Pembelian Konsumen Pada Ahass Cibadak,” Swabumi, vol. 8, no. 2, pp. 118–126, 2020.
[7] S. Anggraeni, M. A. Iha, W. Erawati, and S. Khairunnas, “The Analysis of Sales by Using Apriori and FP-Growth at PT. Panca Putra Solusindo,” REMIK (Riset dan E-Jurnal Manaj. Inform. Komputer), vol. 3, no. 2, pp. 41–46, 2019.
[8] A. R. Wijaya and A. Jananto, “Mencari Pola Pembelian Konsumen Menggunakan Algoritma Fp-Growth,” Din. Inform., vol. 10, no. 1, pp. 1–7, 2018.
[9] K. M. R. A. Utama, R. Umar, and A. Yudhana, “Penerapan Algoritma Fp-Growth Untuk Penentuan Pola Pembelian Transaksi Penjualan Pada Toko Kgs Rizky Motor,” Dinamik, vol. 25, no. 1, pp. 20–28, 2020.
[10] D. E. Putri and E. P. W. Mandala, “Implementasi Algoritma FP-Growth Untuk Menemukan Pola Frekuensi Pembelian Lauk Pada Rumah Makan Takana Juo,” J. Media Inform. Budidarma, vol. 5, no. 1, p. 242, 2021.
[11] M.Hafizh, “Penerapan Data Mining Algoritma Association Rule Metode FP-Growth untuk Menganalisa Tingkat Kekerasan dalam Rumah Tangga,” Maj. Ilm. UPI YPTK, vol. 25, no. 1, pp. 99–106, 2018.
[12] R. Aditiya, S. Defit, and G. W. Nurcahyo, “Prediksi Tingkat Ketersediaan Stock Sembako Menggunakan Algoritma FP-Growth dalam Meningkatkan Penjualan,” J. Inform. Ekon. Bisnis, vol. 2, pp. 67–73, 2020.