ANALYSIS OF MODIFIED K-MEANS CLUSTERING IN DECISION SUPPORT OF INDUSTRIAL PARTNER GROUPING

Billy Sabella, Veri Julianto, Ahmad Rusadi Arrahimi

Abstract


Internship is part of achieving the competencies expected in the educational process. Therefore, the suitability of students to companies that serve as a place for street vendors is something important to pay attention to. Weaknesses in the previous system, there are still many students who are not right in choosing companies/agencies. They are still not paying attention to the competencies expected in this internship process. This study aims to help group industrial partners according to the competency achievements of each department. The method used in this research is Modified K-Means Clustering in the grouping process. While the criteria used are the suitability of the company's field with the department, credibility, company ecosystem, company track record in the field of education, and the facilities provided. In carrying out this work, a system will be developed to process the data resulting from the questionnaire so that groups from each company are obtained. The results of the study were obtained from 86 respondents who were apprentices who had been in 37 companies or agencies. 22 questions that build 7 criteria resulted in 4 stable clusters after 8 iterations.

Keywords: internship, decision support system, Modified K-Means Clustering.



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References


R. Cahyanto, A. R. Chrismanto, and D. Sebastian, “Pengelompokan Komentar Dataset Sentipol dengan Modified K-Means Clustering,” Jurnal Teknik Informatika dan Sistem Informasi, vol. 6, no. 3, Dec. 2020, doi: 10.28932/jutisi.v6i3.3006.

D. N. Ilham and S. Mulyana, “Sistem Pendukung Keputusan Kelompok Pemilihan Tempat PKL mahasiswa dengan Menggunakan Metode AHP dan Borda,” IJCCS (Indonesian Journal of Computing and Cybernetics Systems), vol. 11, no. 1, Jan. 2017, doi: 10.22146/ijccs.16595.

F. Firza and S. Sarjono, “Penerapan Algoritma K-Means Dalam Metode Clustering Untuk Peminatan Jurusan Bagi Siswa Swasta Pelita Raya Kota Jambi,” Jurnal Manajemen Sistem Informasi, vol. 5, no. 3, pp. 371–382, 2020, doi: 10.33998/jurnalmanajemensisteminformasi.2020.5.3.907.

M. W. Talakua, Z. A. Leleury, and A. W. Taluta, “ANALISIS CLUSTER DENGAN MENGGUNAKAN METODE K-MEANS UNTUK PENGELOMPOKKAN KABUPATEN/KOTA DI PROVINSI MALUKU BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA TAHUN 2014,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, vol. 11, no. 2, Dec. 2017, doi: 10.30598/barekengvol11iss2pp119-128.

L. Maulida, “PENERAPAN DATAMINING DALAM MENGELOMPOKKAN KUNJUNGAN WISATAWAN KE OBJEK WISATA UNGGULAN DI PROV. DKI JAKARTA DENGAN K-MEANS,” JISKA (Jurnal Informatika Sunan Kalijaga), vol. 2, no. 3, Mar. 2018, doi: 10.14421/jiska.2018.23-06.




DOI: http://dx.doi.org/10.20527/klik.v9i1.429

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