Quality Assurance in Knowledge Data Warehouse

Authors(5) :-Sri Haryati, Ali Ikhwan, Diki Arisandi, Fadlina, Andysah Putera Utama Siahaan

Knowledge discovery is the process of adding knowledge from a large amount of data. The quality of knowledge generated from the process of knowledge discovery greatly affects the results of the decisions obtained. Existing data must be qualified and tested to ensure knowledge discovery processes can produce knowledge or information that is useful and feasible. It deals with strategic decision making for an organization. Combining multiple operational databases and external data create data warehouse. This treatment is very vulnerable to incomplete, inconsistent, and noisy data. Data mining provides a mechanism to clear this deficiency before finally stored in the data warehouse. This research tries to give technique to improve the quality of information in the data warehouse.

Authors and Affiliations

Sri Haryati
Faculty of Computer Science, Universitas Pembangunan Panca Budi, Medan, Indonesia
Ali Ikhwan
Faculty of Science and Technology, Universitas Islam Negeri Sumatera Utara, Medan, Indonesia
Diki Arisandi
Faculty of Engineering, Department of Informatics, Universitas Abdurrab, Pekanbaru, Indonesia
Fadlina
Department of Informatics Management, AMIK STIEKOM, Medan, Indonesia
Andysah Putera Utama Siahaan
Ph.D. Student of Universiti Malaysia Perlis, Kangar, Malaysia

Data Mining, Knowledge, Data Warehouse

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Publication Details

Published in : Volume 3 | Issue 6 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 239-242
Manuscript Number : IJSRST173658
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Sri Haryati, Ali Ikhwan, Diki Arisandi, Fadlina, Andysah Putera Utama Siahaan, " Quality Assurance in Knowledge Data Warehouse, International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 6, pp.239-242, July-August-2017. Available at doi : 10.32628/IJSRST173658
Journal URL : http://ijsrst.com/IJSRST173658

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