This study examines the relationship between students’ preadmission
academic profile and academic performance. Data
sample of students in the Department of Computer Science in
one of Nigeria private Universities was used. The preadmission
academic profile considered includes ‘O’ level
grades, University Matriculation Examination (UME) scores,
and Post-UME scores. The academic performance is defined
using students’ Grade Point Average (GPA) at the end of a
particular session. Fuzzy Association Rule Mining (FARM)
was used to identify the hidden relationships that exist between
students’ pre-admission profile and academic performance.
This study hopes to determine the academic profile of students
who are most admitted in the session. It determines students’
performance ratings as against their pre-admission academic
profile. This can serve as a predictor for admission committee
to enhance the quality of the new in-take and guide for the
academic advise
