IMPLEMENTASI DATA MINING DENGAN ALGORITMA APRIORI UNTUK MEMPREDIKSI TINGKAT KELULUSAN MAHASISWA

Irham Kurnawan, Fitri Marisa, Purnomo Purnomo

Abstract


Informatics Engineering Program University of Widyagama Malang has many volume of student databases. When properly excavated, so can known patterns or knowledge for a decision-making. Data that can be explored is the understanding of information about graduation students. This research to predict the passing rate of students with more efficient time, which can be known before the student graduated so that can be evaluated in their studies, especially in Informatics Engineering University of Widyagama. In this case using association methods and Apriori algorithm. This method calculates the support value that is the supporting value of an item with big golden rule 60% of the data of course grade. The results of this study to help universities improving the quality of education and help in knowing the information about the graduation rate of students based on the value of the subjects and achievement index obtained by students in Informatics Engineering course University of Widyagama Malang

DOI: https://doi.org/10.26905/jtmi.v4i1.1894


Keywords


Data Mining, Apriori, Tingkat Kelulusan

Full Text:

PDF

References


Hartanto, D., & Hansun, S. (2014). IMPLEMENTASI DATA MINING DENGAN ALGORITMA C4.5 UNTUK MEMPREDIKSI TINGKAT KELULUSAN MAHASISWA. Jurnal ULTIMATICS , 1, 15-20. Dapat diakses di :

[http://www.ejournals.umn.ac.id/index.php/TI/article/view/327.html ].

Wirdasari, D. & A.Calam,.Penerapan Data Mining Untuk Mengolah Data Penempatan Buku Di Perpustakaan Smk Ti Pab 7 Lubuk Pakam Dengan Metode Association Rule. Jurnal SAINTIKOM, 10 (2), 150, 2011. Dapat diakses di :

[http://www.academia.edu/7489155/Penerapan_Data_Mining_Untuk_Mengolah_Data_Penempatan_Buku_Di_Perpustakaan_Smk_Ti_Pab_7_Lubuk_Pakam_Dengan_Metode_Association_Rule].

Linoff , G. S., & Berry, M. J. Data Mining Techniques for Marketing, Sales, Customer Relationship Management. 2011. United States of America: Wiley Publishing, Inc. Dapat diakses di:

[https://www.amazon.com/Data-Mining-Techniques-Relationship-Management/dp/0470650931].

David, Olson, & Yong, Shi. Introduction to Business Data Mining. 2011. International Edision: Mc Graw Hill.

Han, J., & Kamber, M. Data Mining: Concept and Techniques. 2011. Waltham: Elsevier Inc.

Sensuse, G.G., Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Buku Dengan Menggunakan Algoritma Apriori Dan Frequent Pattern Growth (Fp-Growth) : Studi Kasus Percetakan Pt. Gramedia. Jurnal TELEMATIKA MKOM , 4 (1), 118-132, 2012. Dapat diakses di :

[https://journal.budiluhur.ac.id/index.php?journal=teleinformatika&page=index].

Syaifullah, M. A. Implementasi Data Mining Algoritma Apriori Pada Sistem Penjualan. STMIK AMIKOM YOGYAKARTA. 2010. Yogyakarta: Sekolah Tinggi Manajemen Informatika dan Komputer Amikom. Dapat diakses di :

[http://elearning.amikom.ac.id/index.php/karya/752/mardalina,%20se/Implementasi%20data%20mining%20algoritma%20apriori%20pada%20%20sistem%20penjualan].




DOI: https://doi.org/10.26905/jtmi.v4i1.1894

Refbacks

  • There are currently no refbacks.


Copyright (c)



Indexing by:
width="150"

SINTA - Science and Technology Index

Index Copernicus International (ICI)

Tools

Turnitin

crossref

Mendeley

Jurnal Teknologi dan Manajemen Informatika 


Fakultas Teknologi Informasi
University of Merdeka Malang

Alamat:

Jl. Terusan Raya Dieng No. 62-64, Malang, Indonesia, 65146
(0341) 566462
Email: [email protected]


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.