DATA MINING KLASTERISASI PENJUALAN ALAT-ALAT BANGUNAN MENGGUNAKAN METODE K-MEANS (STUDI KASUS DI TOKO ADI BANGUNAN)

  • M. Hasyim Siregar Universitas Islam Kuantan Singingi
Keywords: Data mining, K-Means, Clustering

Abstract

In the world of business competition today, we are required to continually develop business to always survive in the competition. To achieve this there are a few things that can be done is to improve the quality of the product, adding the type of product and operational cost reduction company with how to use data analysis of the company. Data mining is a technology that automate the process to find interesting patterns and sensitive from the large data sets. This allows human understanding about finding patterns and scalability techniques. The store Adi Bangunan is a shop which is engaged in the sale of building materials and household who have such a system on supermarket namely buyers took own goods that will be purchased. Sales data, purchase goods or reimbursed some unexpected is not well ordered, so that the data is only function as archive for the store and cannot be used for the development of marketing strategy. In this research, data mining applied using the model of the process of K-Means that provides a standard process for the use of data mining in various areas used in the classification of because the results of this method can be easily understood and interpreted.

References

E.T. Luthfi, “Penerapan Data Mining Algoritma Asosiasi Untuk meningkatkan penjualan” , JURNAL DASI, ISSN: 1411-3201, Vol. 10, No. 1, Maret 2009.

E. Ikhwan, D. Nofriansyah dan Sriani, “Penerapan Data Mining dengan Algoritma Fp Growth untuk Mendukung Strategi Promosi Pendidikan ( Studi Kasus Kampus STMIK Triguna Dharma)” , Jurnal Ilmiah Saintikom, ISSN : 1978-6603, Vol.14, No. 3, September 2015.

Oyelade, Oladipupo dan Obagbuwa, “Application of k-Means Clustering algorithm for prediction of Students’ Academic Performance” , ISSN 1947-5500, (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, _o. 1, 2010.

S. Khatri dan K. Garg, “Document Clustering Using Improved K-Means Algorithm”, ISSN 2091-2730, International Journal of Engineering Research and General Science Volume 4, Issue 3, May-June, 2016.

Jayant Tikmani, Sudhanshu Tiwari, Sujata Khedkar, “An Approach to Customer Classification using k-means” , ISSN : 2320-9801, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 3, Issue 11, November 2015

J.O. Ong, “Implementasi Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing President University” ISSN 1412-6869, Jurnal Ilmiah Teknik Industri, Vol. 12, No. 1, Juni 2013.

Deepali Virmani ,Shweta Taneja ,Geetika Malhotra, “Normalization based K means Clustering Algorithm” , ISSN: 2349-6495, International Journal of Advanced Engineering Research and Science (IJAERS), [Vol-2, Issue-2, Feb.- 2015].

Published
2018-12-03