Seleksi Atribut Pada Metode Support Vector Machine Untuk Menentukan Kelulusan Mahasiswa E-Learning

Rizqi Agung Permana - STMIK Antar Bangsa

Abstract


Abstract - Learning is a system of web-based communication platform that enables learners, without limitation of time and place, to access a variety of learning tools, such as discussion forums, ratings, content repositories, and document sharing systems. E-Learning can be just as effective as face-to-face in a conventional classroom teaching and learning, if proper teaching techniques and well-organized (Oztekin et al. 2013). Based on the data processing that has been done by comparing the Naive Bayes algorithm, Neural Network, Decision Tree and Machine Support Vector Machine using log data from students. Later in the tests to get the accuracy and AUC values of each algorithm so that the highest test results obtained by using support vector machine.

Keywords: Data Mining, E-Learning, Support Vector Machine.

 

Abstrak - Learning adalah sistem platform komunikasi berbasis web yang memungkinkan peserta didik, tanpa batasan waktu dan tempat, untuk mengakses berbagai alat pembelajaran, seperti forum diskusi, penilaian, repositori konten, dan sistem sharing dokumen. E-Learning bisa sama efektifnya dengan tatap muka dalam pengajaran di kelas konvensional dan belajar, jika teknik mengajar yang tepat dan terorganisir dengan baik (Oztekin et al. 2013). Berdasarkan pengolahan data yang telah dilakukan dengan membandingkan algoritma Naive Bayes, Neural Network, Decision Tree dan Mesin Support Vector Machine menggunakan data log dari siswa. Kemudian di tes untuk mendapatkan akurasi dan AUC nilai masing-masing algoritma sehingga hasil tes tertinggi diperoleh dengan menggunakan mesin dukungan vektor.

Kata kunci: Data Mining, E-Learning, Support Vector Machine.

 



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DOI: https://doi.org/10.31294/evolusi.v4i1.647

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