Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk Perusahaan

Data Mining using Apriori Algorithm for Recommendation of Company Products

Ariefana Ria Riszky -  Department of Informatics, Universitas Mercu Buana, Indonesia
*Mujiono Sadikin -  Department of Informatics, Universitas Mercu Buana, Indonesia
Received: 28 Dec 2018; Revised: 12 Jun 2019; Accepted: 12 Jun 2019; Published: 31 Jul 2019; Available online: 4 Aug 2019.
Open Access Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer
Citation Format:
Article Info
Section: Articles
Language: ID

Supp. File(s):
Data Set
Subject
Type Data Set
  Download (1MB)    Indexing metadata
In Volume 7, Issue 3, Year 2019 (July 2019)
Statistics: 27
Abstract
The implementation of a marketing strategy requires a reference so that promotion can be on target, for example by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items. The purchase transaction dataset was collected in October and November 2018. In the experiment, the minimum value of support is 85% and the minimum confidence value is 90% by processing data using Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on minimum support and confidence values.

Note: This article has supplementary file(s).

Keywords
apriori algorithm; association rule; product recommendation; data mining; product promotion

Article Metrics:

  1. M. Fauzy, K. R. S. W, and I. Asror, “Penerapan Metode Association Rule Menggunakan Algoritma Apriori Pada Simulasi Prediksi Hujan Wilayah Kota Bandung,” J. Ilm. Teknol. Inf. Terap., vol. 13, no. 2, pp. 115–124, 2016.
  2. Fitriyani, “Implementasi Algoritma Fp- Growth Menggunakan Association Rule Pada Market Basket Analysis,” Informatika, vol. II, no. 1, pp. 296–305, 2015.
  3. M. I. Ghozali, R. Z. Ehwan, and W. H. Sugiharto, “Analisa Pola Belanja Menggunakan Algoritma Fp Growth, Self Organizing Map (Som) Dan K Medoids,” vol. 8, no. 1, pp. 317–326, 2017.
  4. S. E. E. Profile, “Sistem Penunjang Keputusan untuk Menentukan Barang Terlaris dengan Algoritma Apriori pada CV Calosa Global Indonesia,” no. December 2017, 2018.
  5. G. I. Marthasari, Y. Azhar, and D. K. Puspitaningrum, “Sistem Rekomendasi Penyewaan Perlengkapan Pesta Menggunakan Collaborative Filtering Dan Penggalian Aturan Asosiasi,” J. Simantec, no. January 2016, 2017.
  6. D. Abdullah and D. Saputra, “Aplikasi Penjadwalan Pengadaan Barang Menggunakan Algoritma Apriori,” no. January, 2016.
  7. R. Buaton, Y. Maulita, and A. Kristiawan, “Korelasi Faktor Penyebab Tindak Kekerasan dalam Rumah Tangga Menggunakan Data Mining Algoritma A Priori,” vol. 14, no. 1, 2018.
  8. A. Ikhwan, Sriani, and D. Nofriansyah, “Penerapan Algoritma Apriori Untuk Menganalisa Transaksi Penjualan Untuk Promo Produk Furniture Jepara,” KeTIK, no. August 2018, 2015.
  9. A. Mauliani, S. Hartati, and A. Musdholifah, “Pembentukan Temporal Association Rules Menggunakan Algoritma Apriori (Studi Kasus:Toko Batik Diyan Solo),” Ijccs, vol. 10, no. 1, pp. 71–80, 2016.
  10. H. D. Hutahaean, B. Sinaga, and A. A. Rajagukguk, “Analisa Dan Perancangan Aplikasi Algoritma Apriori Untuk Korelasi Penjualan Produk ( Studi Kasus : Apotik Diory Farma ),” JIPN(Journal of Informatics Pelita Nusantara), vol. 1, no. 1, pp. 7–13, 2016.
  11. R. I. E. Saragih and H. Sembiring, “Penerapan Algoritma Apriori Data Mining Untuk Mengetahui Kecurangan Skripsi,” no. November, 2017.
  12. G. A. Syaripudin and E. Faizal, “Implementasi Algoritma Apriori Dalam Menentukan Persediaan Obat,” JIKO (Jurnal Inform. dan Komputer), vol. 2, no. 1, 2017.
  13. F. Indriani, “Pola Asosiasi Bahan pada Resep Masakan Daerah dengan Algoritma Apriori,” Semin. Nas. SISFOTEK, vol. 1, no. 1, pp. 119–123, 2017.
  14. W. Aprianti, K. A. Hafizd, and M. R. Rizani, “Implementasi Association Rules dengan Algoritma Apriori pada Dataset Kemiskinan,” Limits J. Math. Its Appl., vol. 14, no. 2, p. 57, 2017.
  15. R. Fitria, W. Nengsih, and D. H. Qudsi, “Implementasi Algoritma Fp-Growth Dalam Penentuan Pola Hubungan Kecelakaan Lalu Lintas,” J. Sist. Inf. (Journal Inf. Syst., vol. 13, no. 2, pp. 11–20, 2017.

Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer License URL: https://creativecommons.org/licenses/by-sa/4.0

The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to JTSiskom journal and Department of Computer Engineering, Universitas Diponegoro as the publisher of the journal. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations. 

JTSiskom journal and Department of Computer Engineering, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in JTSiskom journal are the sole and exclusive responsibility of their respective authors and advertisers.

The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form JTSiskom]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :  

Eko Didik Widianto (Editor-in-Chief)
Editorial Office of Jurnal Teknologi dan Sistem Komputer
Department of Computer Engineering, Universitas Diponegoro
Jl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275
Telp./Fax: +62-24-76480609
Email: jtsiskom@ce.undip.ac.id