PENERAPAN METODE K-MEANS CLUSTERING UNTUK MENENTUKAN CALON MAHASISWA BERPRESTASI

Authors

  • Lidya Rizki Ananda Prodi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Putra Indonesia YPTK Padang

Abstract

It takes such a long time to choose a prospective student achiever. Since the support software has been developed in data processing and presentation of information. On of the ways to solve the problem is by using data mining. Aplicating data mining aims to speed up the process of decision making, which university used to process the student data manually. Data mining is combined with clustering methode by using K-Means algorithm can make the process easier to choose a prospective student achiever, then become a new knowledge and more competitive like for Akademi Manajemen Gunung Leuser Palas Sumatera Sumatera Utara.Keywords : Data Mining, K-means Algorithm, Clustering

References

Fadlina. (2014). “Data Mining untuk Analisa Tingkat Kejahatan Jalanan Dengan Algoritma Association Rule Metode Apriori (Studi Kasus Di Polsekta Medan Sunggal).†Voumel.III No.1.

Ginanjar ,Angga Mabrur, (2012). “Penerapan Data Mining Untuk Memprediksi Kriteria Nasabah Kredit.†Edisi. I Volume. 1.

Lestari Wiji (2013). â€Aplikasi Algoritma Competitive NetworkUntuk Clustering Minat Mahasiswa Terhadap Topik-Topik Penelitian.†ISSN : 2086-9436 Volume 5 Nomor 1.

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Published

2018-12-05

How to Cite

Ananda, L. R. (2018). PENERAPAN METODE K-MEANS CLUSTERING UNTUK MENENTUKAN CALON MAHASISWA BERPRESTASI. Jurnal Inovasi Teknik Informatika, 1(2), 16–19. Retrieved from http://journal.universitaspahlawan.ac.id/index.php/jiti/article/view/28

Issue

Vol. 1 No. 2 (2018): September 2018

Section

Articles

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