Diterbitkan Oleh:
Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.
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. Jurnal Pilar Nusa Mandiri, 15(1), 85-90. https://doi.org/10.33480/pilar.v15i1.113
Article Metrics
Abstract viewed = 2646 times
PDF downloaded = 3082 times
Abstract viewed = 2646 times
PDF downloaded = 3082 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.
An author who publishes in the Pilar Nusa Mandiri: Journal of Computing and Information System agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-NonCommercial 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal
- Author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgement of its initial publication in this journal.
- Author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-NonCommercial 4.0 Licence here: https://creativecommons.org/licenses/by-nc/4.0/.
