Predicting the Number of Joint Admissions and Matriculation Board (JAMB) Applicants into a Public University in Nigeria
Chrysogonus Chinagorom Nwaigwe
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Chukwudi Justin Ogbonna
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Godwin Onyeka Nwafor
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Ugochinyere Ihuoma Nwosu
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Ibrahim Adamu
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Desmond Chekwube Bartholomew *
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
Felix Chikereuba Akanno
Department of Statistics, Federal University of Technology Owerri, Owerri, Imo State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
In Nigeria, the oversight of university education lies with the federal and state governments, as well as private organizations. However, there has been a noticeable decline in the number of applicants seeking admission to public universities through the Joint Admissions and Matriculation Board (JAMB). This trend has raised concerns among public universities in the country. Therefore, this study focuses on one public university in Nigeria to investigate the trend, propose solutions, and forecast future applicant numbers. To analyze and predict the trend, five classical regression models were initially employed. These models were compared, and the best-performing model was identified. Subsequently, the identified classical regression model was compared with a machine learning model known as the Support Vector Regression model. The findings indicate that the Support Vector Regression model exhibited superior performance compared to the Poisson model (the best classical model). The results from the Support Vector Regression model further revealed a potential increase in the future number of JAMB applicants to the University. Therefore, there is need for the university to prepare on how to adequately handle the future suspected potential increase in the number of JAMB applicant. Consequently, the University should establish new competitive courses and enhance the appeal of existing professional courses by increasing their manpower. Furthermore, the University should improve its facilities overall in preparation for the anticipated rise in the number of JAMB applicants in the future.
Keywords: Decline, number of JAMB applicants, causes, predictions, solutions
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