Klasifikasi Batuan Beku Berdasarkan Data Geokimia Menggunakan Algoritma Random Forest Classifier

Muh. Riswan Anas Sukri; Abdi Pangestu

doi:10.30598/tanahgoyang.2.1.52-66

Muh. Riswan Anas Sukri Universitas Pattimura
Abdi Pangestu Universitas Pattimura

DOI: https://doi.org/10.30598/tanahgoyang.2.1.52-66

Abstract

Identifikasi dan klasifikasi batuan berdasarkan karakteristik visual batuan adalah proses yang subjektif dan menggunakan metode yang sama dapat menghasilkan hasil yang berbeda. Pengembangan machine learning telah membuka cara baru untuk mengklasifikasikan batuan. Penelitian ini akan dilakukan untuk mengklasifikasikan batuan beku berdasarkan data geokimia menggunakan algoritma Random Forest Classifier. Random forest adalah algoritma machine learning yang menggunakan kombinasi pohon keputusan untuk membuat prediksi yang akurat guna menentukan cara yang lebih tepat dalam memproses data. Model menunjukkan performa yang cukup baik dengan akurasi 89.4% pada data test. Pada data test, nilai precision berkisar antara 0.75 hingga 1.00, recall antara 0.80 hingga 1.00, dan f1-score antara 0.78 hingga 0.98. Variabel paling penting dalam model klasifikasi batuan ini adalah SIO2_WT%, dengan penurunan skor rata-rata terbesar sekitar 0.30, diikuti oleh MNO_WT% dan FEOT_WT%. Variabel lain memiliki penurunan skor rata-rata yang lebih kecil, menunjukkan kontribusi yang lebih rendah.

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