IMPLEMENTASI ALGORITMA APRIORI TERHADAP DATA PENJUALAN PADA PERUSAHAAN RETAIL
Keywords:
Apriori Algorithm, Transcation Data, Retail, Data Mining
Abstract
The development of the business world is increasingly rapid, so it needs a special strategy to increase the turnover of the company, in this case the retail company. In increasing the company's turnover can be done using the Data Mining process, one of which is using apriori algorithm. With a priori algorithm can be found association rules which can later be used as patterns of purchasing goods by consumers, this study uses a repository of 209 records consisting of 23 transactions and 164 attributes. From the results of this study, the goods with the name CREAM CUPID HEART COAT HANGER are the products most often purchased by consumers. By knowing the pattern of purchasing goods by consumers, the company management can increase the company's turnover by referring to the results of processing sales transaction data using a priori algorithm
Downloads
Download data is not yet available.
References
Arifianti, R. (2016). ANALISIS TATA LETAK DALAM PERSPEKTIF RITEL Ria. AdBispreneur, 1(3), 251–258.
Fauziah, S., & Ratnawati. (2018). Penerapan Metode FIFO Pada Sistem Informasi Persediaan Barang. Jurnal Teknik Komputer, 4(1), 98–108.
GIBRAN, R. (2016). Analisis Aturan Asosiasi Menggunakan Algoritma Apriori Untuk Menentukan Inventori Apotek. Skripsi, Fakultas Ilmu Komputer, (5).
Gunadi, G., & Sensuse, D. I. (2016). Penerapan metode data mining market basket analysis terhadap data penjualan produk buku dengan menggunakan algoritma apriori dan frequent pattern growth (fp-growth): studi kasus percetakan PT. Gramedia. Telematika MKOM, 4(1), 118–132.
Kusrini, & Luthfi, E. T. (2009). Algoritma Data Mining - Kusrini, Emha taufiq luthfi, Universitas Amikom - Google Buku. (Theresia Ari Prabawati, Ed.). C.V ANDI OFFSET. Retrieved from https://books.google.co.id/books?id=-Ojclag73O8C&printsec=frontcover&hl=id#v=onepage&q&f=false
Nursanti, I., & Vydia, V. (2013). Market Basket Analysis Pada Perusahaan, 11(1), 13–22.
Robi Yanto, R. K. (2015). Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat. Implementasi Data Mining Dengan Metode Algoritma Apriori Dalam Menentukan Pola Pembelian Obat, Citec Journal, Vol. 2, No(ISSN: 2354-5771), 102–113. https://doi.org///dx.doi.org/10.4236/ce.2016.71020
Santoso, H., Hariyadi, I. P., & Prayitno. (2016). Data Mining Analisa Pola Pembelian Produk Dengan Menggunakan Metode Algoritma Apriori. Teknik Informatika. ISSN : 2302-3805, (1), 19–24. Retrieved from http://ojs.amikom.ac.id/index.php/semnasteknomedia/article/download/1267/1200
Fauziah, S., & Ratnawati. (2018). Penerapan Metode FIFO Pada Sistem Informasi Persediaan Barang. Jurnal Teknik Komputer, 4(1), 98–108.
GIBRAN, R. (2016). Analisis Aturan Asosiasi Menggunakan Algoritma Apriori Untuk Menentukan Inventori Apotek. Skripsi, Fakultas Ilmu Komputer, (5).
Gunadi, G., & Sensuse, D. I. (2016). Penerapan metode data mining market basket analysis terhadap data penjualan produk buku dengan menggunakan algoritma apriori dan frequent pattern growth (fp-growth): studi kasus percetakan PT. Gramedia. Telematika MKOM, 4(1), 118–132.
Kusrini, & Luthfi, E. T. (2009). Algoritma Data Mining - Kusrini, Emha taufiq luthfi, Universitas Amikom - Google Buku. (Theresia Ari Prabawati, Ed.). C.V ANDI OFFSET. Retrieved from https://books.google.co.id/books?id=-Ojclag73O8C&printsec=frontcover&hl=id#v=onepage&q&f=false
Nursanti, I., & Vydia, V. (2013). Market Basket Analysis Pada Perusahaan, 11(1), 13–22.
Robi Yanto, R. K. (2015). Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat. Implementasi Data Mining Dengan Metode Algoritma Apriori Dalam Menentukan Pola Pembelian Obat, Citec Journal, Vol. 2, No(ISSN: 2354-5771), 102–113. https://doi.org///dx.doi.org/10.4236/ce.2016.71020
Santoso, H., Hariyadi, I. P., & Prayitno. (2016). Data Mining Analisa Pola Pembelian Produk Dengan Menggunakan Metode Algoritma Apriori. Teknik Informatika. ISSN : 2302-3805, (1), 19–24. Retrieved from http://ojs.amikom.ac.id/index.php/semnasteknomedia/article/download/1267/1200
Published
2019-03-07
How to Cite
Putra, J., Raharjo, M., Sandi, T., Ridwan, R., & Prasetyo, R. (2019). IMPLEMENTASI ALGORITMA APRIORI TERHADAP DATA PENJUALAN PADA PERUSAHAAN RETAIL. Pilar Nusa Mandiri : Journal of Computing and Information System, 15(1), 85-90. https://doi.org/10.33480/pilar.v15i1.113
Article Metrics
Abstract viewed = 700 times
PDF downloaded = 711 times
Abstract viewed = 700 times
PDF downloaded = 711 times
Section
Articles
Copyright (c) 2019 Jordy Lasmana Putra, Mugi Raharjo, Tommi Alfian Armawan Sandi, Ridwan, Settings Rizal Prasetyo
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to the PILAR Nusa Mandiri journal as the publisher of the journal, and the author also holds the copyright without restriction.
Copyright encompasses exclusive 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. The reproduction of any part of this journal, its storage in databases, and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with written permission from the PILAR Nusa Mandiri journal.
PILAR Nusa Mandiri journal, the Editors and the Advisory International Editorial Board 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 the PILAR Nusa Mandiri journal are the sole and exclusive responsibility of their respective authors and advertisers.
