Analysis of Data Mining Model for Successful Implementation of Data Warehouse in Tertiary Institutions (A Case Study of Irahim Badamasi Babangida University)
DOI:
https://doi.org/10.32628/CSEIT228531Keywords:
Framework, Information Discovery, Tertiary InstitutionsAbstract
This research work with title “analysis of data mining model for successful implementation of data warehouse in tertiary institutions” is a proposal that provides a framework that is used to structure, plan, and control the process involved in information discovery for tertiary institutions. It equally deals with series of steps or procedures which governs the analysis and design of this particular Data Mining Model for Tertiary Institutions. The methods, techniques and procedures which are used to collect and analyze information were also provided and implemented. Object oriented Analysis and Design methodology (OOADM) was deployed to develop this model. The current system was analysed by using Use Case approach to identify the existing objects in the current system. Use Case diagrams were equally developed and the relationship between the objects was drawn. A diagram was drawn to represent the identified problems. Finally, the High-Level Model (HLM) that would be used to design the proposed system was drawn to enable the System Designer to develop a computer-based model that forecasts educational behaviours with little or no user intervention.
References
- Anthony Danna, Oscar H. Gandy, (2002). Journal of business ethics: All that glitters is not gold Digging Beneath the surface of data mining.
- Cesar V, Javier B, liela S and Alvaro O (2009).Recommendation in Higher Education using data mining techniques, In Proceedings of the Educational Data Mining, conference.
- Fadzilah S. and Abdoulha M., (2009).Uncovering hidden information within University’s Student enrolment data using Data Mining, in proceedings of the third Asia international conference on modelling & simulation conference, IEEE Computer Society. M E. Fayad SJSU-compE L09546 fall (2002).
- Muslihah W., Yuhanim Y., Norshahriah W, Mohd Rizal M., Nor Fatimah A., and Hoo Y. S., (2009). Predicting NDUM Student’s Academic Performance Using Data Mining Techniques, In Proceedings of the Second International Conference on Computer and Electrical Engineering, IEEE Computer Society.
- Naeimeh D., Mohammad S., and Mohammad B, (2004).A New Model for Using Data Mining Technology in Higher Educational Systems in Proceedings of the IEEE Conference.
- Naeimeh D., Mohammad B., and Somnuk P., (2005).Application of Enhance Analysis Model for Data Mining Processes in Higher Educational System, In Proceedings of the ITHET 6th Annual International Conference, IEEE.
- Naeimeh D., Somnuk P., and Mohammad B., Vol. 7, No. 1, pp. 31–54.(2008).Data Mining Application in Higher Learning Institutions, Informatics in Education.
- Nguyen N., Paul J., and Peter H., pp. 7-12, (2007). A Comparative Analysis Techniques for Predicting Academic Performance in Proceedings of the 37th ASEE/IEEE Frontiers in Education Conference.
- Pathom P, Anongnart S, and Prasong P.(2008). Comparisons of Classifier Algorithms: Bayesian Network, C4.5, Decision Forest and NBTree for Course Registration Planning Model of Undergraduate Students, Sripatum University Chonburi Campus, Office of Computer Service, Chonburi Thailand, IEEE.
- Ramaswami M., and Bhaskaran R., Vol. 7, Issue 1, No. 1, (2010). CHAID Based Performance Prediction Model in Educational Data Mining, IJCSI International Journal of Computer Science Issues.
- Tissera R, Athauda I, and Fernando C.(2006). Discovery of Strongly Related Subjects in the Undergraduate Syllabi using Data Mining, ICIA, IEEE.
- Witten, I, Frank E.(2000).Data Mining. Academic Press.
- Yiming M, Bing L, Ching W., Philip Y., and Shuik L., (2000).Targeting the Right Students using Data Mining, ACM.
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