Perbandingan Metode SOM/Kohonen dengan ART 2 pada Data Mining Perusahaan Retail

Abstract— This study investigates the performance of artificial neural network method on clustering method. Using UD. Fenny’s customer profile in year 2009 data set with the Recency, Frequency and Monetary model data. Clustering methods were compared in this study is between the Self Organizing Map and Adaptive Resonance Theory 2. The performance evaluation method validation is measured by the index cluster validation. Validation index clusters are used, among others, Davies-Bouldin index, index and index Dunn Silhouette. The test results show the method Self Organizing Map is better to process the data clustering. Index term— Data Mining, Artificial Neural Network, Self Organizing Map, Adaptive Resonance Theory 2. Intisari—Penelitian ini ingin mengetahui unjuk kerja metode clustering data berbasis jaringan saraf tiruan. Menggunakan data set profil pelanggan UD. Fenny tahun 2009 dengan atribut Recency, Frequency dan Monetary. Metode clustering yang dibandingkan pada penelitian ini adalah Self Organizing Map dan Adaptive Resonance Theory 2. Evaluasi kinerja metode dilakukan dengan mengukur validasi index dari cluster yang terbentuk. Validasi cluster yang digunakan antara lain Indeks Davies-Bouldin, Indeks Dunn dan Indeks Silhouette. Hasil pengujian menunjukkan metode Self Organizing Map lebih baik dalam melakukan proses clustering data. Kata Kunci— Data Mining, Jaringan Saraf Tiruan Self Organizing Map, Adaptive Resonance Theory 2.