Pemetaan Kompetensi Siswa Untuk Mengikuti Seleksi Lomba Kejuruan Multimedia Menggunakan Metode K-Means

Abstract

The process of mapping competent students who will take part in the competition is the selection of students who have the best scores in the vocational field, which is carried out by the academic side in order to include students who are competent in the vocational field to be included in the vocational competition. So far, the school still has difficulties in selecting competent and less competent students due to the limitations of the presentation and processing of the data carried out. To facilitate the mapping of competent students in the vocational field, this activity is computerized into software. Time accuracy and effectiveness are important factors so that the mapping process of competent students can run well and as it should. In this research, an application is made that can cluster competent students so that they can take part in Multimedia vocational competitions appropriately and accurately using the K-Means Algorithm. It applies variables such as Academic Values and Attitude Values.

Keywords

Clusterization, Competent Students, Competition; algorithm k-means

References

Agustin Ely Rahayu, Khoiril Hikmah, Nanik Yustia Ningsih, Abd. Charis Fauzan (2019) Penerapan K-Means Clustering Untuk Penentuan Klasterisasi Beasiswa Bidikmisi Mahasiswa ILKOMNIKA: Journal of Computer Science and Applied Informatics Vol. 1, No. 2, Desember 2019, Halaman 82-86

Ai Ilah Warnilah (2016) ANALISIS ALGORITMA K-MEANS CLUSTERING UNTUK PEMETAAN PRESTASI SISWA STUDI KASUS SMP NEGERI I SUKAHENING Indonesian Journal on Computer and Information Technology Vol 1 No 1 Mei 2016

Budi Santosa, 2007, Data Mining (Teori dan Aplikasi), Graha Ilmu, Yogyakarta.

Edhy Sutanta (2011:91). Basis Data Dalam Tinjauan Konseptual

Fitri Larasati Sibuea & Andy Sapta (2017). PEMETAAN SISWA BERPRESTASI MENGGUNAKAN METODE K-MEANS CLUSTERING JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol. IV No. 1, Des 2017, hlm. 85 92.

Green F Mandias, Green A Sandag, Susi Susanti, dan Haryanto Reza Musak (2017) Penerapan Algoritma K-Means Untuk Analisis Prestasi Akademik Mahasiswa Fakultas Ilmu Komputer Universitas Klabat Cogito Smart Journal/VOL. 3/NO. 2/DEC 2017

Hamdan Yuwafi, Fitri Marisa, Indra Darma Wijaya (2019) IMPLEMENTASI DATA MINING UNTUK MENENTUKAN SANTRI BERPRESTASI DI PP.MANAARULHUDA DENGAN METODE CLUSTERING ALGORITMA K-MEANS Jurnal SPIRIT Vol. 11 No. 1 Mei 2019, hal 22 29

Jaroji, Danuri, Fajri Profesio Putra (2016). K-MEANS UNTUK MENENTUKAN CALON PENERIMA BEASISWA BIDIK MISI DI POLBENG JURNAL INOVTEK POLBENG - SERI INFORMATIKA, Vol. 1, No. 1 , Juni 2016.

Lidya Rizki Ananda,S.kom, M.kom (2018) PENERAPAN METODE K-MEANS CLUSTERING UNTUK MENENTUKAN CALON MAHASISWA BERPRESTASI JITI, Vol.1, No. 2, September 2018

Lukman Hakim (2019) PERANCANGAN APLIKASI PENILAIAN MAHASISWA BERPRESTASI UNIVERSITAS XYZ MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Jurnal SITECH, Vol 2, No 1, Juni 2019

Nur Jannah, Tony Yulianto (2016). Mengelompokkan Siswa Berprestasi Akademik dengan Menggunakan Metode K Means Kelas VII MTs Hidayatul Mubtadiin Pancoran Kadur

Risa Helilintar, Intan Nur Farida (2018) Penerapan Algoritma K-Means Clustering Untuk Prediksi Prestasi Nilai Akademik Mahasiwa Jurnal Sains dan Informatika Volume 4, Nomor 2, November 2018

Raymond McLeod, Jr, George P. Schell (2007). Management Information System (Sistem Informasi Manajemen), Prentice Hall.

Sugiyono. (2016). Metode Penelitian dan Pengembangan (Research and Development/R&D). In Bandung: Alfabeta.

Syaiful Bahri Djamarah. (2012). Prestasi Belajar Dan Kompetensi Guru. Surabaya: Usaha Nasional.

Tan, P.N., Steinbach, M., Kumar, V. (2006). Introduction to Data Mining. Boston:Pearson Education

DOI: https://doi.org/10.36350/jbs.v12i2.151

Article metrics

Abstract views : 175 | views : 204

Refbacks

  • There are currently no refbacks.