PEMAKAIAN METODE ASOSIASI DALAM DATA MINING UNTUK PENJUALAN LEBIH DARI SATU JENIS PRODUK PADA PERUSAHAAN

  • Herman Mulyana Manajemen Informatika AMIK BSI Jakarta
Keywords: Data Mining, Metode Asosiasi, Penjualan Produk

Abstract

Growing information technology and cheap makes companies have to use it. At the company, especially the marketing division, sale, and purchase also use computer facilities to support its activities. Transactions that occur every day is done with the use of computers to collect a lot of data that is usually often treated simply as data records history alone so it does not have much value for the progress of the business. The business competition requires companies to find strategies that can improve product sales. This strategy can be obtained from the analysis and processing of data records method or the appropriate rules so as to produce useful information, for example in the form of patterns of relationships or linkages that occur mainly on product sales data. The pattern of relationship or association rules can be found and formed with the help of data mining methods in the association. This data linkage patterns are becoming more valuable to the company. This pattern is used by more optimally supported by the results of the calculation of the ratio of the support and confidence levels so that the pattern can be seen how powerful it can be used based on existing data. The pattern of relationships which have become commonly sold product information along with sales of other products can be used to provide a proposal for the company's marketing strategy to directly offer other products that are usually sold in conjunction with the sale of a product with a high level of confidence and can reduce the cost of promotion because they do not need to promote or offer all kinds of products available to the buyer or customer but sufficiently related products and has the potential to be sold. The end results the company can sell more types of products to buyers and customers by effectively and efficiently.

Downloads

Download data is not yet available.

References

Gunadi, Goldie, Dana Indra Sensuse. 2012. Penerapan Metode Data Mining

Market Basket Analysis terhadap Data Penjalan Produk Buku dengan

menggunakan algoritma Apriori dan Frequent Pattern Growth (FPGrowth): Studi Kasus Percetakan PT. Gramedia. Jakarta: Jurnal Telematika

MKom Volume 4 No.1 ISSN: 2085-725X. Akses: 22 Nopember 2013,

http://pascasarjana.budiluhur.ac.id/wpcontent/uploads/2013/02/Goldie_Dana_TM-Vol4-No1.pdf

Han, Jiawei dan Micheline Kamber. 2006. Data Mining: Concepts and techniques. San Francisco, USA: Morgan Kaufmann Publishers.

Huda, Nuqson Masykur. 2010. Aplikasi Data Mining untuk menampilkan informasi tingkat kelulusan mahasiswa (Studi Kasus di Fakultas MIPA Universitas Diponegoro). Semarang: Fakultas MIPA, Universitas Diponegoro. Akses: 31 Juli 2011. http://eprints.undip.ac.id/23168/1/

TA_NUXON_J2F005280.pdf

Larose, Daniel T. 2005. Discovering knowledge in data: An introduction to

data mining. New Jersey, USA: Wiley-Interscience, John Wiley & Sons Inc.

Luthfi, Emha Taufiq. 2009. Penerapan Data Mining algoritma asosiasi untuk

meningkatkan penjualan. Yogyakarta: Jurnal DASI ISSN: 1411-3201 Vol. 10 No. 1. Akses: 31 Juli 2011, http://p3m.amikom.ac.id/p3m/dasi/201

/DASIMaret2009/5 - STMIK AMIKOM YOGYAKARTA - PENERAPAN DATA MINING ALGORITMA ASOSIASI UNTUK MENINGKATKAN PENJUALAN.pdf

Pramudiono, Iko. 2003. Pengantar Data Mining: Menambang Permata

Pengetahuan di Gunung Data. Akses: 31 Juli 2011, http://www.ilmukomputer.org/wpcontent/uploads/2006/08 /ikodatamining.zip.

Radhiaty, Nurullah Husufa, Juningsi D.F.J. Letik, Tri Wahyu W. dan I. Wayan

Simri Wicaksana. 2009. Personifikasi Web E-Commerce Menggunakan

Basket Algoritma dari Data Mining.Depok. Proceeding PESAT Volume 3

ISSN: 1858-2559 Universitas Gunadarma. Akses: 25 Nopember 2013, 725X. Akses: 22 Nopember 2013, http://pascasarjana.budiluhur.ac.id/wpcontent/uploads/2013/02/Goldie_Dana_TM-Vol4-No1.pdf

Han, Jiawei dan Micheline Kamber. 2006. Data Mining: Concepts and techniques. San Francisco, USA: Morgan Kaufmann Publishers.

Huda, Nuqson Masykur. 2010. Aplikasi Data Mining untuk menampilkan informasi tingkat kelulusan mahasiswa (Studi Kasus di Fakultas MIPA Universitas Diponegoro). Semarang: Fakultas MIPA, Universitas Diponegoro. Akses: 31 Juli 2011. http://eprints.undip.ac.id/23168/1/TA_NUXON_J2F005280.pdf

Larose, Daniel T. 2005. Discovering knowledge in data: An introduction to data mining. New Jersey, USA: Wiley-Interscience, John Wiley & Sons Inc.

Luthfi, Emha Taufiq. 2009. Penerapan Data Mining algoritma asosiasi untuk meningkatkan penjualan. Yogyakarta: Jurnal DASI ISSN: 1411-3201 Vol. 10 No. 1. Akses: 31 Juli 2011, http://p3m.amikom.ac.id/p3m/dasi/2010/DASIMaret2009/5 - STMIK AMIKOM YOGYAKARTA -PENERAPAN DATA MININGALGORITMA ASOSIASI UNTUK MENINGKATKAN PENJUALAN.pdf

Pramudiono, Iko. 2003. Pengantar Data Mining: Menambang Permata Pengetahuan di Gunung Data. Akses: 31 Juli 2011, http://www.ilmukomputer.org/wpcontent/uploads/2006/08/ikodatamining.zip.

Radhiaty, Nurullah Husufa, Juningsi D.F.J. Letik, Tri Wahyu W. dan I. WayanSimri Wicaksana. 2009. Personifikasi Web E-Commerce Menggunakan Basket Algoritma dari Data Mining. Depok. Proceeding PESAT Volume 3 ISSN: 1858-2559 Universitas Gunadarma. Akses: 25 Nopember 2013, Akses: 31 Juli 2011, http://uppm.ilkom.unsri.ac.id/userfiles/ JurnalVol_5_No_1_Januari_2010 /7BayuAdhiTama.pdf

Yusuf W., Yogi, F. Rian Pratikto dan Gerry T. 2006. Penerapan Data Mining dalam penentuan aturan asosiasi antar jenis item. Yogyakarta, Indonesia:Seminar Nasional Aplikasi Teknologi Informasi ISSN: 1907-5022. Akses: 31 Juli 2011,http://journal.uii.ac.id/index.php/Snati/article/view/1502/ 1283, 1502-1341-1PB.pdf
Published
2014-03-15
How to Cite
Mulyana, H. (2014). PEMAKAIAN METODE ASOSIASI DALAM DATA MINING UNTUK PENJUALAN LEBIH DARI SATU JENIS PRODUK PADA PERUSAHAAN. Jurnal Pilar Nusa Mandiri, 10(1), 47-55. https://doi.org/10.33480/pilar.v10i1.462