CLUSTER ANALYSIS FOR LEARNING STYLE OF VOCATIONAL HIGH SCHOOL STUDENT USING K-MEANS AND FUZZY C-MEANS (FCM)

Abstrak

Abstrak

Ketidakmampuan siswa dalam menyerap berbagai pengetahuan bukan dikarenakan ketidakmampuannya pemahamanan bukan pula karena guru tidak mampu mengajar, melainkan lebih dikarenakan ketidak cocokan gaya belajar (learning style) antara siswa dan guru, sehingga siswa merasa tidak nyaman belajar pada guru, hal tersebut terjadi juga di Sekolah Menengah Kejuruan, penelitian untuk menganalisa cluster (kelompok) tipe belajar siswa dengan menerapkan metode data mining yaitu K-means dan Fuzzy C-means (FCM). Tujuan ingin dicapai adalah mengetahui keefektifan clustering tipe belajar ini terhadap perkembangan daya serap dan peningkatan prestasi belajar siswa. Dalam penelitian ini metode yang digunakan dimulai dari tahap data cleaning, data selection, data transformation, pemambangan data, pattern evolution, dan pengembangan pengetahuan (knowledge). Hasil Penelitian didapatkan dengan mengunakan metode K-Means dan FCM dapat dibentuk 4 cluster yaitu tipe belajar audio dan visual, tipe belajar visual dan audio, tipe belajar visual serta tipe belajar kinestetis dan audio.

Kata kunci : Data mining, tipe belajar, clustering, FCM, K-means

Abstract

The inability of students to absorb the various knowledge conveyed by the teacher is not due to the inability of his understanding and not because the teacher is not able to teach, but rather due to the incompatibility of learning styles (learning style) between students and teachers, so that students feel uncomfortable learning to certain teachers, it occurred also in Vocational High School Student, research to analyze cluster (group) type of student learning by applying data mining method that is K-means and Fuzzy C-means (FCM). The goal to be achieved is to know the effectiveness of this type of learning clustering on the development of absorptive capacity and improvement of student achievement. In this research, the method used to cluster the learning type with data mining process starting from data cleaning, data selection, data transformation, data mining, pattern evolution, and knowledge (knowledge). The result of the research was obtained by using K-Means and FCM method can be shown 4 clusters which are combination of auditory and visual learning style, visual and auditory style, only visual style and kinesthetic and auditory style.