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)
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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 > 20101-(S2) Master Thesis |
| 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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