The Association Rule Methods and K-Means Clustering For Optimization Mapping Of New Students Admission
Author:
Affiliation:
1. Universitas Amikom Yogyakarta,Magister of Informatics Engineering,Yogyakarta,Indonesia
2. Universitas Amikom Yogyakarta,Computer Science Faculty,Yogyakarta,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10511274/10512358/10513089.pdf?arnumber=10513089
Reference18 articles.
1. Analysis and Prediction of Students’ Academic Performance Based on Educational Data Mining
2. Educational Data Mining Utilization to Support the Admission Process in Higher Education Institutions: A Systematic Literature Review
3. Analyzing Applicant’s Pre-admission data and Predicting Applicant’s Performance in Pre-Admission Test using Data Mining Techniques
4. Improve the Accuracy of Students Admission at Universities Using Machine Learning Techniques
5. Research on the Professional Identity of Undergraduates Majoring in Preschool Education of Connection between Secondary Vocational Education and Undergraduate Higher Education
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