Analisis Algoritma Dbscan Dalam Menentukan Parameter Epsilon Pada Clustering Data Numerik
Abstract
Algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise) merupakan salah satu algoritma clustering yang berbasis numerik, pada algoritma ini digunakan data numerik sebagai pengujiannya. Algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise) memiliki kelemahan yaitu sulitnya menentukan nilai Epsilon yang sesuai agar diperoleh hasil clustering yang baik. Pada algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise), nilai epsilon dihitung berdasarkan banyak data dari keseluruhan data yang dijui. Pada penelitian ini dilakukan modifikasi terhadap algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise) dengan melakukan penentuan nilai epsilon , hasil yang diperoleh pada penelitian nilai Euclidean Distance yang diperoleh lebih baik bila dibandingkan dengan hasil yang diperoleh dari algoritma algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise) biasa.
Kata Kunci: DBSCAN, Clustering, Euclidean Distanc, Epsilon.
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