Analisis Algoritma C4.5 Dan Fuzzy Sugeno Untuk Optimasi Rule Base Fuzzy
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Abstract
Logika fuzzy dapat mengatasi ketidakmampuan matematika konvensional untuk model sistem nonlinear. Fuzzy sugeno merupakan salah satu metode yang sering digunakan dalam logika fuzzy. Penggunaan metode sugeno dapat mengatasi masalah sistem non linear. Kelemahan dari logika fuzzy adalah meningkatnya beban komputasi yang bertambah secara eksponensial seiring dengan bertambahnya jumlah variabel dan jumlah aturan dalam logika fuzzy. Beberapa cara telah dilakukan oleh para peneliti sebelumnya untuk mengurangi beban komputasi, diantaranya dengan mengurangi sejumlah aturan dalam logika fuzzy. Mengurangi sejumlah aturan akan berdampak pada tingkat akurasi fuzzy yang berkurang. Pada penelitian ini, menggunakan algoritma C4.5 sebagai optimasi rule fuzzy. Hasil perbandingan metode fuzzy sugeno yang diintegrasikan dengan algoritma C4.5 mendapatkan hasil akurasi sebesar 88,57 %. Jumlah luaran yang awalnya 288 rule menjadi hanya 57 rule, hal tersebut menyebabkan beban komputsi berkurang. Disamping beban komputasi yang berkurang, hal tersebut berdampak pada berkurangnnya tingkat akurasi.
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