Clustering Penerima Beasiswa Yayasan Untuk Mahasiswa Menggunakan Metode K-Means

 (*)Bernadus Gunawan Sudarsono Mail (Universitas Bung Karno, Jakarta, Indonesia)
 Sri Poedji Lestari (Universitas Bung Karno, Jakarta, Indonesia)

(*) Corresponding Author

Submitted: December 14, 2020; Published: January 22, 2021

DOI: http://dx.doi.org/10.30865/mib.v5i1.2670

Abstract

Grouping of scholarship recipients Scholarship assistance will be made based on the accumulated value using clustering where the scholarship recipients will be given scholarships with different amounts and sizes, because scholarships from foundations are limited and have levels of distribution. The division of groups to students who receive scholarships from foundations uses the clustering method of data mining where the function of clustering is a cluster or the task of grouping something is using the clustering algorithm approach, namely the K-means algorithm. The results of this clustering show that students based on their groups are divided into four groups based on the number of criteria, the results of the grouping show the number and decision of the foundation on granting foundation scholarships to students.

Keywords


Clustering; K-Means; Scholarship Grantee

Full Text:

PDF


Article Metrics

Abstract View: 73 times | PDF View: 29 times

References

H. S. Tambunan, I. Gunawan, and S. Sumarno, “Prediksi Jumlah Pendapatan Beasiswa PPA dan BBP Menggunakan Jaringan Syaraf Tiruan Backpropagation,” J. Media Inform. Budidarma, vol. 3, no. 4, p. 346, 2019, doi: 10.30865/mib.v3i4.1327.

A. P. Utomo, “Pemodelan Arsitektur Enterprise Sistem Informasi Akademik Pada Perguruan Tinggi Menggunakan Enterprise Architecture Planning,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 5, no. 1, p. 33, 2014, doi: 10.24176/simet.v5i1.129.

R. Taufiq and H. P. Sari, “Rancang Bangun Sistem Pendukung Keputusan Penentuan Jenis Beasiswa Menggunakan Knn,” J. Tek. Univ. Muhammadiyah Tangerang, vol. 8, no. 1, pp. 6–10, 2019.

M. Mariko and A. Yaqin, “Sistem Pendukung Keputusan Penentuan Calon Penerima Beasiswa Prestasi di Universitas Amikom Yogyakarta,” J. Media Inform. Budidarma, vol. 3, no. 3, p. 172, 2019, doi: 10.30865/mib.v3i3.1180.

Assrani dkk., “Penentuan Penerima Bantuan Siswa Miskin Menerapkan Metode Multi Objective Optimization on The Basis of Ratio Analysis (MOORA),” JURIKOM (Jurnal Ris. Komputer), vol. 5, no. 2407–389X (Media Cetak), pp. 1–5, 2018.

S. A. Rahmah, “Klasterisasi Pola Penjualan Pestisida Menggunakan Metode K-Means Clustering ( Studi Kasus Di Toko Juanda Tani Kecamatan Hutabayu Raja ),” J. Inf. Technol. Res., vol. 1, no. 1, pp. 1–5, 2020.

K. D. Maisari, D. Andreswari, and R. Efendi, “Implementasi Metode TOPSIS dengan Pembobotan Entropy untuk Penentuan Calon Penerima Bantuan Siswa Miskin (BSM) APBD Kota Bengkulu( Studi Kasus : SMAN 8 Kota Bengkulu ),” J. Rekursif, vol. 5, no. 2, pp. 179–194, 2017.

A. Aditya, I. Jovian, and B. N. Sari, “Implementasi K-Means Clustering Ujian Nasional Sekolah Menengah Pertama di Indonesia Tahun 2018/2019,” J. Media Inform. Budidarma, vol. 4, no. 1, p. 51, 2020, doi: 10.30865/mib.v4i1.1784.

N. Rofiqo, A. P. Windarto, and D. Hartama, “Penerapan Clustering Pada Penduduk Yang Mempunyai Keluhan Kesehatan Dengan Datamining K-Means,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 2, no. 1, pp. 216–223, 2018, doi: 10.30865/komik.v2i1.929.

E. Sugiyarti and A. Maseleno, “Sistem Pendukung Keputusan (Dss) Penyeleksian Pemilihan Penerima Beasiswa Sma N 1 Ulubelu Tanggamus Mengunakan Data Mining,” Konf. Mhs. Sist. Inf., vol. 6, no. 1, pp. 62–69, 2018.

D. N. Hidayat, “Dikotomi Kualitatif – Kuantitatif Dan Varian Paradigmatik Dalam Penelitian Kualitatif,” Scriptura, vol. 2, no. 2, pp. 81–94, 2009, doi: 10.9744/scriptura.2.2.81-94.

R. Rahim, E. Buulolo, and N. Silalahi, “C4.5 Algorithm To Predict The Impact Of The Earthquake,” no. January, pp. 2–8, 2017, doi: 10.31227/osf.io/rbwmg.

D. Evanko, “Optical imaging of the native brain,” Nat. Methods, vol. 7, no. 1, p. 34, 2010, doi: 10.1038/nmeth.f.284.

D. P. Utomo, “Analisis Komparasi Metode Klasifikasi Data Mining dan Reduksi Atribut Pada Data Set Penyakit Jantung,” vol. 4, no. April, pp. 437–444, 2020, doi: 10.30865/mib.v4i2.2080.

R. S. Harahap, “Komparasi Algoritma Klasifikasi Decision Tree, Naive Bayes Dan Neural Network Untuk Prediksi Penyakit Ginjal Kronis,” Konf. Nas. Ilmu Pengetah. dan Teknol., vol. 2, no. 1, pp. 239-INF.244, 2016, [Online]. Available: http://konferensi.nusamandiri.ac.id/prosiding/index.php/knit/article/view/129.

S. Defiyanti, “Integrasi Metode Clustering dan Klasifikasi untuk Data Numerik,” Citee, no. July, pp. 256–261, 2017.

E. Buulolo, Buku Data Mining Untuk Perguruan Tinggi, I. 2020.

F. L. Gaol, T. Matsuo, and S. City, “The Digital Transformation of Enterprise Architecture on Culinary SMEs : A Case Study – Culinary SMEs in DKI Jakarta Province,” vol. 14, no. 2, pp. 275–289, 2020.

N. Rofiqo, A. P. Windarto, and D. Hartama, “KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) PENERAPAN CLUSTERING PADA PENDUDUK YANG MEMPUNYAI KELUHAN KESEHATAN DENGAN DATAMINING K-MEANS,” [Online]. Available: http://ejurnal.stmik-budidarma.ac.id/index.php/komik.

J. Han, M. Kamber, and J. Pei, “Data Mining: Concepts and Techniques,” Data Min. Concepts Tech., 2012, doi: 10.1016/C2009-0-61819-5.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Clustering Penerima Beasiswa Yayasan Untuk Mahasiswa Menggunakan Metode K-Means

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 JURNAL MEDIA INFORMATIKA BUDIDARMA

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



JURNAL MEDIA INFORMATIKA BUDIDARMA
STMIK Budi Darma
Sekretariat : Jln. Sisingamangaraja No. 338 Telp 061-7875998
email : mib.stmikbd@gmail.com

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