Commenced in January 2007
Paper Count: 31435
Using Data Mining Technique for Scholarship Disbursement
Abstract:This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1108480Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1758
 L. Chang, “Applying data mining to predict college admissions yield: A case Study” New Directions for Institutional Research, 2006, pp.53–68. doi: 10.1002/ir.187.
 S. S. Aksenova, D. Zhang, and M. Lu, “Enrollment prediction through data Mining”, in Information Reuse and Integration, 2006 IEEE International Conference. Retrieved on 01/13/2009. Available at http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4018543.
 J. Luan, and C. Zhao, “Practicing data mining for enrollment management and beyond”, in J. Luan & C. Zhao (Eds.), New Direction for Institutional Research, 2006, no.131. San Francisco: Jossey-Bass. W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123–135.
 P. Eykamp, “Using data mining to explore which students use placement to reduce time to degree”, in J. Luan and C. Zhao (Eds.), New Direction for Institutional Research, 2006, no. 131. San Francisco: Jossey-Bass.
 M. Goyal and R. Vohra, “Applications of Data Mining in Higher Education”, in International Journal of Computer Science Issues (IJCSI), Vol. 9, Issue 2, No 1, March 2012 ISSN (Online): 1694-0814 www.IJCSI.org
 T. Silwattananusarn, and K. Tuamsuk, “Data Mining and Its Applications for Knowledge Management : A Literature Review from 2007 to 2012,.International Journal of Data Mining and Knowledge Management Process (IJDKP) Vol.2, No.5, September 2012, Pp 13-24.