DOI: https://doi.org/10.14710/j.gauss.v11i2.35475

GUI R UNTUK ANALISIS KERANJANG BELANJA DENGAN ALGORITMA APRIORI PADA SUATU PERUSAHAAN E-COMMERCE

*Ryan Anugrah  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tatik Widiharih  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Sugito Sugito  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2022 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
Technological developments help people live easier. One of the technological developments is being able to trade digitally or it can be called e-commerce. To increase revenue, e-commerce companies collect consumer sales history data that can be analyzed and obtain information about consumer habits. One of the analyzes that can be used is shopping basket analysis which aims to find a pattern in transaction data. In data processing and analysis is done using the R program computation and GUI R is made with a recommendation system simulation. The results of the shopping cart analysis produce as many as 22 rules using a minimum support of 0.06 and a confidence of 0.5. The greater the support value, the more often the product or rule is purchased by consumers from all data transactions and vice versa. Meanwhile, the greater the trust value, the more often the products purchased under the regulation are purchased together. Thus, the information can be used to help carry out promotions to increase sales by the company.
Fulltext View|Download
Keywords: Data Mining; Association Rule; Market Basket Analysis; Algorithm Apriori; E-commerce

Article Metrics:

Article Info
Section: Articles
Recent articles
PEMODELAN TOPIK PADA KELUHAN PELANGGAN MENGGUNAKAN ALGORITMA LATENT DIRICHLET ALLOCATION DALAM MEDIA SOSIAL TWITTER GUI R UNTUK ANALISIS KERANJANG BELANJA DENGAN ALGORITMA APRIORI PADA SUATU PERUSAHAAN E-COMMERCE PERAMALAN HARGA EMAS DUNIA DENGAN MODEL GLOSTEN-JAGANNATHAN-RUNCLE GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY More recent articles
  1. Agrawal, C. C. 2016. Recommender Systems: The Textbook. New York: Springer
  2. Berry, M. W., Browne, M. 2006. Lecture Notes in Data Mining. Singapore: World Scientific Publishing Co. Pte. Ltd
  3. Haryanto, D., Oslan, Y., Dwiyana, D. 2011. Implementasi Analisis Keranjang Belanja Dengan Aturan Asosiasi Menggunakan Algoritma Apriori Pada Penjualan Suku Cadang Motor. Jurnal Buana Informatika Vol. 2, No. 2 : Hal 81-94
  4. Hermawati, F. A. 2013. Data Mining. Yogyakarta: ANDI
  5. Kurniawan, F. et al. 2018. Market Basket Analysis to Identify Customer Behaviours by Way of Transaction Data. Knowledge Engineering and Data Science Vol. 1, No. 1 : Hal 20-25
  6. Limbong, T. 2019. E-Commerce: Implementasi, Strategi dan Inovasinya. Medan: Yayasan Kita Menulis
  7. Linoff, G. S., Berry, M. J. A. 2011. For Marketing, Sales, and Customer Relationship Management. Canada: Wiley Publishing, Inc
  8. Listriani, D., Setyaningrum, A. H., Eka, F. 2016. Penerapan Metode Asosiasi Menggunakan Algoritma Apriori pada Aplikasi Analisa Pola Belanja Konsumen (Studi Kasus Toko Buku Gramedia Bintaro). Jurnal Teknik Informatika Vol. 9, No. 2 : Hal 120–127
  9. Mundir. 2012. Statistik Pendidikan. Jember: STAIN Jember Press
  10. Prasetya, C. S. D. 2017. Sistem Rekomendasi Pada E-Commerce Menggunakan K-Nearest Neighbor. Jurnal Teknologi Informasi dan Ilmu Komputer Vol. 4, No 3: Hal 194-200
  11. Prasetyo, N. A., Alhaq, A. M. G., Bramanto, T. 2020. Jurus Praktis Satistik Dasar dan Penggunaan R Commander. Banyumas: CV. Pena Persada
  12. Ruth, Z. 2003. E-Commerce and E-Business. Manila : E-ASEAN Task Force ; Kuala Lumpur : UNDP-APDIP
  13. Santoso, P. B. and Hamdani, M. 2007. Stasistika Deskriptif dalam Bidang Ekonomi dan Niaga. Jakarta: Erlangga
  14. Soliman, F., Youssef, M. A. 2003. Internet-based e-commerce and its impact on manufacturing and business operations. Industrial Management and Data Systems Vol. 103, No. 8–9 : Hal 546–552
  15. Susanto, S., Suryadi, D. 2010. Pengantar Data Mining. Yogyakarta: ANDI
  16. Tampubolon, K., Saragih, H., Reza, B. 2013. Implementasi Data Mining Algoritma Apriori pada Sistem Persediaan Alat-Alat Kesehatan. Informasi dan Teknologi Ilmiah Vol. 1, No. 1 : Hal 93-106
  17. Tan, P.-N., Steinbach, M., Kumar, V. 2006. Introduction to Data Mining. Boston: Pearson Education
  18. Tirta, I. M. 2015. Panduan Penyusunan Modul dan Analisis Data Online Berbasis Web Interaktif menggunakan R dalam Rangka Melengkapi K Statistika Virtual (Online, Interaktif, Terintegrasi). Jember: Universitas Jember

Last update:

No citation recorded.

Last update:

No citation recorded.