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An Enhanced System for Allocation of Resources in Nigerian Universities

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Rhoda Ikono, Abimbola Babalola, Olaronke Iroju, Ishaya Gambo
10.5120/ijca2017914556

Rhoda Ikono, Abimbola Babalola, Olaronke Iroju and Ishaya Gambo. An Enhanced System for Allocation of Resources in Nigerian Universities. International Journal of Computer Applications 168(11):35-41, June 2017. BibTeX

@article{10.5120/ijca2017914556,
	author = {Rhoda Ikono and Abimbola Babalola and Olaronke Iroju and Ishaya Gambo},
	title = {An Enhanced System for Allocation of Resources in Nigerian Universities},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {11},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {35-41},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume168/number11/27922-2017914556},
	doi = {10.5120/ijca2017914556},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Education is a fundamental right and access to higher education plays a vital role in shaping an individual’s career in life. However, the process of securing admission into Nigerian universities is highly competitive. This is because the population of students who seek admission into Nigerian Universities annually is exponential. Nevertheless, one of the majors of securing admission into Nigerian Universities is through the pre-degree program. This process is however manually done, time consuming and fraught with errors. Consequently, this paper designs an enhanced system that automatically allocates courses to students seeking admission into Nigerian Universities through the pre-degree program. The system uses artificial neural network for its decision making capabilities. This will help to eliminate bias that unaided human judgment is prone to during admission process.

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Keywords

Resource Allocation System, Course of Study, Pre-Degree, Resource Allocation.