Implementation Association Rules with Apriori Algorithm of Student Attendance Record in Islamic University of Indonesia

Authors

  • Rachmad Febrian Statistics Department, Faculty of Mathematics and Natural Sciences, Islamic University of Indonesia (UII), 55584 Sleman, Yogyakarta, Indonesia)
  • Ayundyah Kesumawati Statistics Department, Faculty of Mathematics and Natural Sciences, Islamic University of Indonesia (UII), 55584 Sleman, Yogyakarta, Indonesia)

DOI:

https://doi.org/10.31763/ijabis.v1i2.2

Keywords:

Data Mining, Association Rules, Student Attendance Record

Abstract

Data has become an indispendable part of every subject in the world such as in economy, industry, business function, individual and also organization in education such as in university. Data mining software is one of a number of analytical tools for analyzing data. One of techniques in data mining is Association Rules. This paper aim is to known the association between student attendance record and 3 variable which are course, time, and credit semester. Student attendance record need to be analyzed due to see the effectiveness of student attendance record. The result of this paper, association rules is the best method for this case. Courses is not significant for association rules because didn’t present in output. There are 9 rules that has lift ration beyond 1.0000000.

Downloads

Published

2018-01-05

How to Cite

Febrian, R., & Kesumawati, A. (2018). Implementation Association Rules with Apriori Algorithm of Student Attendance Record in Islamic University of Indonesia. International Journal of Applied Business and Information Systems, 1(2), 1–5. https://doi.org/10.31763/ijabis.v1i2.2

Issue

Section

Articles