Implementasi Data Warehouse dan Data Mining: Studi Kasus Analisis Peminatan Studi Siswa

Authors

  • Eka Miranda Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v2i1.2705

Keywords:

specialization studies, data warehousing, data mining

Abstract

This paper discusses the implementation of data mining and their role in helping decision-making related to students’ specialization program selection. Currently, the university uses a database to store records of transactions which can not directly be used to assist analysis and decision making. Based on these issues then made the data warehouse design used to store large amounts of data and also has the potential to gain new data distribution perspectives and allows to answer the ad hoc question as well as to perform data analysis. The method used consists of: record analysis related to students’ academic achievement, designing data warehouse and data mining. The paper’s results are in a form of data warehouse and data mining design and its implementation with the classification techniques and association rules. From these results can be seen the students’ tendency and pattern background in choosing the specialization, to help them make decisions.

 

Dimensions

Plum Analytics

References

Azimah, A., Suyahco, D., Giri, Y. (2007). Implementasi Data Warehouse untuk Menunjang Kegiatan Akademik. Seminar Nasional Sistem dan Informatika.

Buja, A., Lee, Y. (2001). Data mining criteria for tree-based regression and classification. International Conference on Knowledge Discovery and Data Mining, 27-36.

Chang, C., Chen, R. (2006). Using data mining technology to solve classification problems: A case study of campus digital library. The Electronic Library, 03, 307-321.

Chen, S.Y., Liu, X. (2005). Data mining from 1994 to 2004: an application-oriented review. International Journal of Business Intelligence and Data Mining, 01 (01), 4-11.

Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P. (1996), The KDD process for extracting useful knowledge from volumes of data. Communications of the ACM, 39 (11), 07-34.

Han, J., Kamber, M. (2001), Data Mining: Concepts and Techniques. San Mateo, CA: Morgan Kaufmann.

Mallach, E. G. (2000). Decision Support and Data Warehouse Systems. United States: McGraw-Hill

Wah, T. Y., Peng, N. H., Hok, C. S. (2007). Building Data Warehouse. Proceedings of the 24th South East Asia Regional Computer Conference.

Yu, S.C., Chen, R.S. (2001). Developing an XML Framework for an Electronic Document Delivery System. The Electronic Library, 19 (20), 102-110.

Downloads

Published

2011-06-01

Issue

Section

Articles
Abstract 519  .
PDF downloaded 669  .