Seleksi Fitur Information Gain dan Teknik Pruning Untuk Memperbaiki Akurasi Algoritma C4.5 dalam Kasus Keterlambatan Biaya Kuliah
DOI:
https://doi.org/10.30872/jim.v17i2.11794Keywords:
Data mining, Klasifikasi, C4.5, information gain, pruning, optimasi, keterlambatan biaya kuliah,Abstract
Penerapan biaya kuliah memiliki peranan yang sangat penting di suatu universitas untuk dapat meningkatkan mutu dan infrastruktur pendidikan khususnya di Universitas Muhammadiyah Kalimantan Timur (UMKT). Namun, dalam pelaksanaannya masih banyak mahasiswa yang terlambat dalam melakukan pembayaran biaya kuliah. Hal ini dapat mengganggu UMKT dalam sisi operasional dan pelaksanaan peningkatan mutu serta infrastruktur. Pada penelitian ini akan dilakukan penentuan fitur, penerapan algoritma C4.5, dan evaluasi kinerja algoritma C4.5 dengan menggunakan confusion matrix pada pembagian data 90% data training dan 10% data testing. Untuk mengoptimasi kinerja algoritma C4.5, pada penelitian ini akan diterapkan seleksi fitur menggunakan metode information gain dan pruning. Penelitian ini menggunakan data yang diperoleh dari Biro Administrasi Keuangan dan Biro Administrasi Akademik UMKT dengan jumlah data sebanyak 12.408. Hasil pengujian kinerja algoritma C4.5 tanpa menggunakan seleksi fitur information gain dan teknik pruning memperoleh nilai akurasi sebesar 61,40%. Adapun hasil pengujian kinerja algoritma C4.5 dengan menggunakan seleksi fitur information gain dan teknik pruning memperoleh hasil sebesar 64,86%. Hasil pengujian kinerja algoritma C4.5 dengan menggunakan seleksi fitur information gain dan teknik pruning terbukti mampu meningkatkan kinerja algoritma sebesar 3,45% pada kasus keterlambatan biaya kuliah.
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