Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan

Data Mining using Apriori Algorithm for Product Recommendation for Customers

Ariefana Ria Riszky  -  Department of Informatics, Universitas Mercu Buana, Indonesia
*Mujiono Sadikin orcid scopus  -  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.
DOI: https://doi.org/10.14710/jtsiskom.7.3.2019.103-108 View
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Abstract
The implementation of a marketing strategy requires a reference so that promotion can be on target, such as 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 for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the 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 defined minimum support and confidence values.

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

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  1. S. D. Cahyo, “Sistem Rekomendasi Pembuatan Paket Menu dengan Market Basket Analysis Menggunakan Algoritma Apriori pada Rumah Makan Kampung Laut Semarang,” B. Thesis, Universitas Dian Nuswantoro, Semarang, Indonesia, 2017. [online]
  2. F. Fitriyani, “Implementasi Algoritma Fp- Growth Menggunakan Association Rule Pada Market Basket Analysis,” Jurnal Informatika, vol. 2, 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,” Simetris: Jurnal Teknik Industri, Mesin, Elektro dan Ilmu Komputer, vol. 8, no. 1, pp. 317-326, 2017.
  4. G. I. Marthasari, Y. Azhar, and D. K. Puspitaningrum, “Sistem Rekomendasi Penyewaan Perlengkapan Pesta Menggunakan Collaborative Filtering dan Penggalian Aturan Asosiasi,” Jurnal Simantec, vol. 5, no. 1, pp. 1-8, 2015.
  5. S. Widjaya, “Sistem Penunjang Keputusan untuk Menentukan Barang Terlaris dengan Algoritma Apriori pada CV Calosa Global Indonesia,” J-Intech: Journal of Information and Technology, vol. 5, no. 2, pp. 139-146, 2017.
  6. R. Buaton, Y. Maulita, and A. Kristiawan, “Korelasi Faktor Penyebab Tindak Kekerasan dalam Rumah Tangga Menggunakan Data Mining Algoritma A Priori,” Jurnal Media Infotama, vol. 14, no. 1, pp. 21-30, 2018.
  7. F. Indriani, “Pola Asosiasi Bahan pada Resep Masakan Daerah dengan Algoritma Apriori,” SISFOTEK, vol. 1, no. 1, pp. 119-123, 2017.
  8. W. Aprianti, K. A. Hafizd, and M. R. Rizani, “Implementasi Association Rules dengan Algoritma Apriori pada Dataset Kemiskinan,” Limits: Journal of Mathematics and Its Applications, vol. 14, no. 2, pp. 145-155, 2017.
  9. H. D. Hutahaean, B. Sinaga, and A. A. Rajagukguk, “Analisa Dan Perancangan Aplikasi Algoritma Apriori Untuk Korelasi Penjualan Produk (Studi Kasus : Apotik Diory Farma),” Journal of Informatics Pelita Nusantara, vol. 1, no. 1, pp. 7-13, 2016.
  10. R. I. E. Saragih and H. Sembiring, “Penerapan Algoritma Apriori Data Mining Untuk Mengetahui Kecurangan Skripsi,” Majalah Ilmiah Methoda, vol. 5, no. 2, pp. 1-7, 2015.
  11. M. Fauzy, K. R. Saleh, and I. Asror, “Penerapan Metode Association Rule Menggunakan Algoritma Apriori Pada Simulasi Prediksi Hujan Wilayah Kota Bandung,” Jurnal Ilmiah Teknologi Informasi Terapan, vol. 13, no. 2, pp. 221-227, 2016.
  12. A. Ikhwan, Sriani, and D. Nofriansyah, “Penerapan Algoritma Apriori Untuk Menganalisa Transaksi Penjualan Untuk Promo Produk Furniture Jepara,” in Konferensi Nasional Pengembangan Teknologi Informasi dan Komunikasi, Medan, Indonesia, 2015, pp. 19-24.
  13. G. A. Syaripudin and E. Faizal, “Implementasi Algoritma Apriori Dalam Menentukan Persediaan Obat,” JIKO (Jurnal Inform. dan Komputer), vol. 2, no. 1, pp. 10-14, 2017.
  14. I. Djamaludin, “Analisis Pola Pembelian Konsumen pada Transaksi Penjualan Menggunakan Algoritma Apriori,” Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, vol. 8, no. 2, pp. 671-678, 2017.
  15. R. Fitria, W. Nengsih, and D. H. Qudsi, “Implementasi Algoritma Fp-Growth Dalam Penentuan Pola Hubungan Kecelakaan Lalu Lintas,” Jurnal Sistem Informasi, vol. 13, no. 2, pp. 11-20, 2017.

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