Authors :
Nurul Abdillah; Syaiful Zuhri Harahap; Ade Parlaungan Nasution
Volume/Issue :
Volume 5 - 2020, Issue 12 - December
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3nxjLyn
Abstract :
Graduation rate is one of the parameters of
the effectiveness of educational institutions. The decrease
in student graduation rate affects college accreditation.
University database stores student administration and
academic data, if explored appropriately using data
mining techniques, it can be known patterns or
knowledge to make decisions. The naive bayes algorithm
aims to measure the level of accuracy to be applied in the
case of student graduation timeliness. The Naive Bayes
method is a classifier with probability and statistical
methods to predict future opportunities based on past
experience. This research uses student data of
Informatics Engineering Education program of Padang
State University class of 2011. The variables used in this
study were: NIM, name, gender, entry status, GPA, area
of origin and employment status. Based on the test
results by measuring the performance of the method, it
is known that naive bayes has a good accuracy value of
93.48%. From the accuracy value can be concluded that
the algorithm naive bayes have a good performance in
predicting the timeliness of student graduation.
Graduation rate is one of the parameters of
the effectiveness of educational institutions. The decrease
in student graduation rate affects college accreditation.
University database stores student administration and
academic data, if explored appropriately using data
mining techniques, it can be known patterns or
knowledge to make decisions. The naive bayes algorithm
aims to measure the level of accuracy to be applied in the
case of student graduation timeliness. The Naive Bayes
method is a classifier with probability and statistical
methods to predict future opportunities based on past
experience. This research uses student data of
Informatics Engineering Education program of Padang
State University class of 2011. The variables used in this
study were: NIM, name, gender, entry status, GPA, area
of origin and employment status. Based on the test
results by measuring the performance of the method, it
is known that naive bayes has a good accuracy value of
93.48%. From the accuracy value can be concluded that
the algorithm naive bayes have a good performance in
predicting the timeliness of student graduation.
