IMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI DATA PESERTA DIDIK

Authors

  • Imam Sutoyo Teknologi Informasi Universitas Bina Sarana Informatika Jakarta

DOI:

https://doi.org/10.33480/pilar.v14i2.70

Keywords:

Algoritma Data Mining, Decission Tree, C45, Classification Algorithm, CRISP-DM Methodology, Random Forest

Abstract

Klasifikasi peserta didik bertujuan untuk mengelompokkan peserta program pendidikan agar kegiatan pembelajaran dapat disesuaikan dengan kelompok-kelompok tersebut. Metode tradisional untuk melaksanakan klasifikasi ini adalah dengan mengurutkan peserta didik menggunakan satu atribut, yaitu nilai akhir mereka kemudian membagi mereka berdasarkan ukuran tertentu. Metode yang lebih baik adalah dengan menggunakan algoritma Data Mining yang mampu menggunakan lebih dari satu atribut. Pada penelitian ini, algoritma Decision Tree digunakan untuk melaksanakan klasifikasi. Metodologi yang digunakan adalah CRISP-DM. Algoritma Decision Tree yang diujicoba adalah C4.5 dan Random Forest. Validasi dilaksanakan menggunakan 10-Fold Cross Validation untuk dicari algoritma yang memberikan akurasi paling tinggi. Berdasarkan percobaan, didapatkan hasil bahwasanya Decission Tree C.45 memberikan hasil terbaik dengan akurasi 96,73 %. Oleh karena itu, pada tahap Deployment dari metodologi CRISP-DM, model dan rule dari C4.5 digunakan untuk membuat aplikasi untuk klasifikasi ini.

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How to Cite

Sutoyo, I. (2018). IMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI DATA PESERTA DIDIK. Jurnal Pilar Nusa Mandiri, 14(2), 217–224. https://doi.org/10.33480/pilar.v14i2.70

Issue

Vol. 14 No. 2 (2018): Pilar Nusa Mandiri : Journal of Computing and Information System Periode September 2018

Section

Articles

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