Implementasi Metode SVM-PSO Dengan Fitur Selection Variance Threshold Pada Klasifikasi Penyakit Diabetes Mellitus
DOI:
https://doi.org/10.26555/jim.v10i2.30877Keywords:
SVM-PSO ,, Variance Threshold,, Klasifikasi ,, Diabetes Mellitus,, Optimasi ,Abstract
Pada penelitian ini membahas tentang kasus klasifikasi pada data penyakit diabetes. Metode yang digunakan dalam penelitian ini adalah metode Support Vector Machine yang dioptimalkan dengan algoritma Particle Swarm Optimization guna memperoleh parameter terbaik dengan kombinasi seleksi fitur menggunakan Variance Threshold. Penelitian ini bertujuan untuk mengetahui cara kerja dan hasil akurasi dari metode Support Vector Machine dengan optimasi Particle Swarm Optimization menggunakan seleksi fitur Variance Threshold. Hasil penelitian menggunakan kombinasi metode tersebut menunjukkan hasil akurasi sebesar 80%. Hasil akurasi tersebut lebih tinggi jika dibandingkan dengan metode Support Vector Machine tunggal tanpa optimasi dan seleksi fitur dengan akurasi sebesar 76%. Meningkatkan akurasi sebesar 4% dari 76% menjadi 80%.
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