Pola Beli Konsumen Menggunakan Algoritma Fp-Growth Untuk Rekomendasi Promosi Pada Aneka Jaya Motor

Authors

  • Junta Zeniarja Universitas Dian Nuswantoro
  • Kurniawan Ridwan Surohardjo Universitas Dian Nuswantoro
  • Agus Winarno Universitas Dian Nuswantoro

DOI:

https://doi.org/10.33633/joins.v6i1.4493

Abstract

A piece of appropriate information can create and establish a business strategy in increasing sales through technology that can affect the trade-in buying and selling goods with the data information generated can be calculated in detail and accurately. At Aneka Jaya Motor Semarang, this was triggered by the demand for competition. One solution is a product promotion target. For determining which items are feasible for promotion, the application of a promotional decision recommendation system is made using data mining techniques associated with FP-Growth algorithms, its function is to find items that are often purchased simultaneously by consumers. Data used in the form of transaction data with the total amount used 501 data. The results obtained by appearing 1 rule is if consumers buy spark plug parts then buy oil parts with minimum support of 10% and minimum confidence of 35%. The lift ratio obtained is 1 so that valid rules are generated.

Author Biography

Junta Zeniarja, Universitas Dian Nuswantoro

Computer Science

References

S. Kasus and P. T. Rosalia, “SISTEM REKOMENDASI PEMESANAN SPAREPART DENGAN ALGORITMA FP-GROWTH,” pp. 6–7, 2016.

W. N. Ismail, M. M. Hassan, and H. A. Alsalamah, “Context-Enriched Regular Human Behavioral Pattern Detection from Body Sensors Data,” IEEE Access, vol. 7, no. 1, pp. 33834–33850, 2019.

O. Stit, J. Riffi, A. Yahyaouy, and H. Tairi, “Comparative Study of Different Association Rule Methods,” in Colloquium in Information Science and Technology, CIST, 2018, vol. 2018-Octob, pp. 323–327.

Islamiyah, P. L. Ginting, N. Dengen, and M. Taruk, “Comparison of Priori and FP-Growth Algorithms in Determining Association Rules,” in ICEEIE 2019 - International Conference on Electrical, Electronics and Information Engineering: Emerging Innovative Technology for Sustainable Future, 2019, pp. 320–323.

M. M. Hasan and S. Zaman Mishu, “An Adaptive Method for Mining Frequent Itemsets Based on Apriori and FP Growth Algorithm,” in International Conference on Computer, Communication, Chemical, Material and Electronic Engineering, IC4ME2 2018, 2018, pp. 1–4.

F. Ren, Z. Pei, and K. Wu, “Selection of satisfied association rules via aggregation of linguistic satisfied degrees,” IEEE Access, vol. 7, pp. 91518–91534, 2019.

A. Abdullah, “Rekomendasi Paket Produk Guna Meningkatkan Penjualan Dengan Metode FP-Growth,” vol. 4, no. 1, pp. 21–26, 2018.

M. Fauzy, K. R. Saleh W, and I. Asror, “Penerapan Metode Association Rule Menggunakan,” J. Ilm. Teknol. Inf. Terap., vol. II, no. 2, pp. 221–227, 2016.

M. Kadafi, “Penerapan Algoritma FP-GROWTH untuk Menemukan Pola Peminjaman Buku Perpustakaan UIN Raden Fatah Palembang,” Matics, vol. 10, no. 2, p. 52, 2019.

N. A. Hasibuan, N. Silalahi, S. D. Nasution, D. U. Sutiksno, H. Nurdiyanto, and E. Buulolo, “IMPLEMENTASI DATA MINING UNTUK PENGATURAN LAYOUT MINIMARKET DENGAN MENERAPKAN ASSOCIATION RULE,” vol. 4, no. 4, pp. 6–11, 2017.

L. W. Basalamah and N. Ransi, “IMPLEMENTASI ALGORITMA FREQUENT PATTERN GROWTH PADA APLIKASI RETAIL BERBASIS JAVA,” vol. 3, no. 1, pp. 67–80, 2017.

T. P. Hong, C. Y. Lin, W. M. Huang, K. S. M. Li, L. S. L. Wang, and J. C. W. Lin, “Using Tree Structure to Mine High Temporal Fuzzy Utility Itemsets,” IEEE Access, vol. 8, pp. 153692–153706, 2020.

I. Astrina, M. Z. Arifin, and U. Pujianto, “Penerapan Algoritma FP-Growth dalam Penentuan Pola Pembelian Konsumen pada Kain Tenun Medali Mas,” Matrix J. Manaj. Teknol. dan Inform., vol. 9, no. 1, pp. 32–40, 2019.

E. Faisal, J. Zeniarja, and D. A. N. Sa’adah, “Pola Beli Konsumen menggunakan Algoritma FP-Growth untuk Rekomendasi Promosi penjualan pada Batik Nadya Pekalongan,” in SeNTIK - STMIK JAKARTA STI&K, 2017.

D. Fitriati, “Implementasi Data Mining untuk Menentukan Kombinasi Media Promosi Barang Berdasarkan Perilaku Pembelian Pelanggan Menggunakan Algoritma Apriori,” in Annual Research Seminar 2016, 2016, vol. 2, no. 1, pp. 472–480.

A. Irawan, Rudianto, and R. Desiana, “Prototype Sistem Informasi Bursa Kerja pada Universitas Serang Raya,” J. Sensi Strateg. Educ. Inf. Syst., vol. 7, no. 1, pp. 36–52, 2021.

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Published

2021-05-31

How to Cite

[1]
J. Zeniarja, K. R. Surohardjo, and A. Winarno, “Pola Beli Konsumen Menggunakan Algoritma Fp-Growth Untuk Rekomendasi Promosi Pada Aneka Jaya Motor”, Journal of Information System, vol. 6, no. 1, pp. 48–55, May 2021.