TY  - JOUR
T1  - A Fuzzy-Mining Predictive Model for Analysing Student’s Academic Performance
AU - Oladipupo, Olufunke AU - Ehigbochie, Amenawon 
JO  - International Journal of Soft Computing
VL  - 12
IS  - 4
SP  - 210
EP  - 217
PY  - 2017
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2017.210.217
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2017.210.217
KW  - Academic performance
KW  -socio-economic factors
KW  -fuzzy association rule mining algorithm
KW  -fuzzy model
KW  -data mining
KW  -triangular membership function
AB  - In recent years, serious concerns have been expressed about the alarming rate of weak academic
performance of students. A number of factors have been attributed to this trend. To this effect, this study
analyzed the syndicate effect of some socio-economic factors: student’s interest, relationship status,
entrepreneurial activities, peer influence, health and family background on academic performance. Fuzzy mining
approach was used to capture interesting patterns about the socio-economic factors and the student academic
performance. Questionnaire approach was used to harvest student’s level of involvement in the listed factors
in quantitative measure. The questionnaire represented the student’s opinions from 2 public and 2 private
universities in Nigeria. The involved students are from 200 level and above, so as to accommodate for
experience in the university system. Fuzzy association rule mining algorithm with triangular membership
function was used for the mining process and fuzzy models. The result shows various hidden previously
unknown patterns of student’s involvement and the effect on their academic performance. This study interprets
the patterns according to their inference as regards student academic performance. This, we hope will help
institutions to monitor the student’s academic performances with regard to these socio-economic factors and
also serve as an indicator of measure for the students.
ER  -