Klastering siswa sekolah menengah kejuruan (SMK) menggunakan metode fuzzy c-means

Wahyono, Amin (2015) Klastering siswa sekolah menengah kejuruan (SMK) menggunakan metode fuzzy c-means. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Students new reception is an annual event a good school level Primary School, Junior High School and High School and Vocational High School. This activity is a process of selecting students who have diverse backgrounds and competencies. During this way is done in selecting prospective students to fill the class with superior category and regular classes by looking at the number of national test scores alone, it is certainly not represent a prospective student competence. In this study attempted to explore other core competencies of a prospective student arranged in report cards, diplomas, certificates activities and early entrance exams. With Fuzzy C-Means algorithm, diverse competence of prospective students can be grouped in detail in accordance with the competencies that students have. This clustering results will be the basis to put prospective students entering a superior class or regular class. By forming a community of superior class and a regular class, there is a new climate in the strategy and expected results of learning methods and learning process comfortable, fun and competitive. Cluster evaluation carried out by the method of cohesion and sparasi. Cohesion shows the closeness of competence of students in a cluster, while sparasi shows the difference in quality between clusters superior class and a regular class. Evaluation of cluster based index PCI (Partition Coefficient) = 0.8472 (Very Good), and Partition Entropy index (PEI) 0.3797 (Good) =============================================================================================================== Students new reception is an annual event a good school level Primary School, Junior High School and High School and Vocational High School. This activity is a process of selecting students who have diverse backgrounds and competencies. During this way is done in selecting prospective students to fill the class with superior category and regular classes by looking at the number of national test scores alone, it is certainly not represent a prospective student competence. In this study attempted to explore other core competencies of a prospective student arranged in report cards, diplomas, certificates activities and early entrance exams. With Fuzzy C-Means algorithm, diverse competence of prospective students can be grouped in detail in accordance with the competencies that students have. This clustering results will be the basis to put prospective students entering a superior class or regular class. By forming a community of superior class and a regular class, there is a new climate in the strategy and expected results of learning methods and learning process comfortable, fun and competitive. Cluster evaluation carried out by the method of cohesion and sparasi. Cohesion shows the closeness of competence of students in a cluster, while sparasi shows the difference in quality between clusters superior class and a regular class. Evaluation of cluster based index PCI (Partition Coefficient) = 0.8472 (Very Good), and Partition Entropy index (PEI) 0.3797 (Good)

Item Type: Thesis (Masters)
Additional Information: RTE 004.35 Wah k
Uncontrolled Keywords: Calon Peserta Didik Baru (PPDB); Fuzzy C-Means; Kelas Unggul; SMK (Sekolah Menengah Kejuruan)
Subjects: Q Science > QA Mathematics > QA278.55 Cluster analysis
Divisions: Faculty of Electrical Technology > Electrical Engineering > (S2) Master Theses
Depositing User: - Taufiq Rahmanu
Date Deposited: 28 Jun 2019 02:57
Last Modified: 28 Jun 2019 02:57
URI: http://repository.its.ac.id/id/eprint/63346

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