Penerapan Algoritma K-Means Dan C4.5 Untuk Clustering Jurusan Siswa Baru Pada Sekolah Menengah Kejuruan (Studi Kasus: SMK Negeri 1 Paron)

SALSABILLA, AZZAHRA and , Azizah Fatmawati, S.T., M.Cs. (2021) Penerapan Algoritma K-Means Dan C4.5 Untuk Clustering Jurusan Siswa Baru Pada Sekolah Menengah Kejuruan (Studi Kasus: SMK Negeri 1 Paron). Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

Courses in Vocational High Schools (SMK) are used as a reference to channel the abilities of students. The cornering is done during the registration of new students. In general, prospective students must choose a major by the average score of the report card or national test scores of Junior High School (SMP) regardless of other criteria resulting in the occurrence of mistakes in the selection of majors that are not by their interests and abilities. This research aims to classify courses for students appropriately, effectively, and efficiently. The method used in this study is with Data Mining which applies K-Means Algorithm and C4.5 Algorithm. K-Means algorithm is used to group courses based on supporting criteria in the form of junior high school grades, namely Math and Language Scores, average parental income, and several prospective students' siblings. The results of the K-Means algorithm will be compared to the results of the C4.5 algorithm in the form of a rule (decision tree). This study produced an accuracy value from K-Means algorithm by 58,22%, while the C4.5 algorithm resulted in an Accuracy value of 41,61%, Precision of 26,44%, and Recall value of 25,9%.

Item Type: Karya ilmiah (Skripsi)
Uncontrolled Keywords: Algoritma C4.5, Algorima K-Means, Klasifikasi, Kriteria, Penjurusan
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika
Depositing User: AZZAHRA SALSABILLA
Date Deposited: 06 Aug 2021 00:09
Last Modified: 06 Aug 2021 00:09
URI: http://eprints.ums.ac.id/id/eprint/92604

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