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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Eri Timothy Napitupulu
Universitas Prima Indonesia
Computer Science & IT

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PERBANDINGAN ALGORITMA K-MEANS DAN X-MEANS UNTUK MENGELOMPOKKAN MINAT KEJURUAN SISWA BARU PADA SMK MULTIKARYA MEDAN MENGGUNAKAN METODE CLUSTERING Tajrin Tajrin; Eri Timothy Napitupulu; Fine Aldi Jous Nainggolan
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.933

Abstract

Abstract Education is one of the decisive aspects in producing the nation's successor. This can be seen from science, especially at the Vocational High School (SMK) level. Determining a student's major is not an easy thing, many parents and their own children do not know their interests and abilities. Determining a major is a process of focusing students on a particular field of concentration, this is done so that each individual can learn more in lessons that are in accordance with concentration and direct each individual to develop their abilities and interests. Majoring is expected to maximize every potential or talent possessed. SMK Multikarya is one of the schools in Medan city that has 8 majors, namely Multimedia, Automotive Light Vehicle Engineering, Computer and Network Engineering, Machining Engineering, Motorcycle Engineering and Business, Accounting and Institutional Finance, Software Engineering and Office Automation and Governance. Where every year SMK Multikarya always accepts 450 students. This results in the school always having difficulty in determining students who do not have a major. One way to make it easier to determine SMK majors is data mining with a comparison of the K-Means and X-Mean Clustering algorithms. In testing the k-means and x-means algorithms can produce the best K-Means algorithm because it produces the lowest value of 0.413 or 41%.
Co-Authors Fine Aldi Jous Nainggolan Tajrin Tajrin