Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063
Gede Candra Adi Pranata
Universitas Pendidikan Ganesha
Computer Science & IT Education

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PENGEMBANGAN APLIKASI DATA MINING INFORMASI TINGKAT KELULUSAN MAHASISWA MENGGUNAKAN ALGORITMA APRIORI Gede Candra Adi Pranata; I Gede Mahendra Darmawiguna; Made Windu Antara Kesiman
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 3 No. 3 (2014)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v3i3.19760

Abstract

Good student graduation level is the desire of every University. In order to get a better graduation rate, understanding of the student’s value is needed. In this case, some of the issues related to the student will be examined to get a connection to the student’s graduation rate. This study aims to process the data in order to display the student parent relationship with graduation rates. Mining methods and algorithms priori are used in this study.Data mining method is a method which is used to process many data. The purpose of this method is to generate information from a priori algorithm. Priori algorithm is data retrieval algorithms using associative rules (Association rule) to determine the associative relationships of a combination of items. Association Rule is conducted through a calculation of the support and confidence of a relationship item. An association rule will be interesting if the value is greater than the minimum support and confidence value is greater than the minimum confidence.The result of this study is software called Application Graduation. Based on test result of the software, it was found that the Application Graduate student registration information could create relationship between data and student graduation rates.
Co-Authors I Gede Mahendra Darmawiguna Made Windu Antara Kesiman