Perancangan Data Warehouse dan Penerapan Teknik Clustering Spatial pada Wesel: Studi Kasus PT XXX

Authors

  • Arief Dwi Hartadi Bina Nusantara University
  • Oktalia Juwita Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v4i1.2704

Keywords:

competitive advantage, Data Warehouse, clustering technique, spatial database,

Abstract

By setting up the right service and product for the customer, the company may increase its marketing effectiveness as well as sales. For that purpose, information on company’s product and sales is highly needed in order to help on decision making process, which expectedly enables company to create value and eventually gain competitive advantage. This research attempts to develop a Data warehouse for PT XXX, which is expected to exhibit useful information for the company without disturbing its operational system. The Data warehouse is developed with Oracle 11g. Apart from that, this research also aims to gather information and knowledge with spatial database. The data mining is conducted by using WEKA application, which compares the algorithm of DBSCAN, K-Means, and EM clustering. Data mining from the spatial data is expected to create area map which indicates sales rate of PT Pos Indonesia’s products. Through this it is hoped that the company may focus more in marketing certain product with particular advantage in one particular area to produce effectiveness. The research outcome indicates that the Data warehouse being developed has already managed to exhibit the receipt report of postal money order (wesel pos), retail stock, as well as retail sales. 

Dimensions

Plum Analytics

References

Handojo, Andreas dan Rostianingsih, Silvia. (2004). Pembuatan Data Warehouse Pengukuran Kinerja Proses Belajar Mengajar di Jurusan Teknik Informatika Universitas Kristen Petra. Jurnal Informatika, 5(1), 53-58.

O’Brien, James A. (2003). Introduction to Information System: Essential for the e-Business Enterprise (Eleventh Edition). New York: McGraw-Hill Irwin.

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Published

2013-06-30

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