IMPLEMENTASI DATA MINING DENGAN ALGORITMA APRIORI UNTUK MEMPREDIKSI TINGKAT KELULUSAN MAHASISWA

Authors

  • Irham Kurnawan Jurusan Teknik Informatika, Universitas Widyagama Malang
  • Fitri Marisa Jurusan Teknik Informatika, Universitas Widyagama Malang
  • Purnomo Purnomo Jurusan Teknik Informatika, Universitas Widyagama Malang

DOI:

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

Keywords:

Data Mining, Apriori, Tingkat Kelulusan

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

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].

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Published

2018-01-23

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