MODIFIKASI K-MEANS BERBASIS ORDERED WEIGHTED AVERAGING (OWA) UNTUK KASUS KLASTERING
ABSTRACT: K-means clustering
method based on Ordered Weighted Averaging (OWA) was developed by Cheng et al
(2009) to resolve problem in classification using integrating k-means
clustering and OWA. K-means clustering is a method of clustering and OWA is an
aggregation operator. OWA was able to reduce the complexity of experimental
data and helpin representing sophisticated relationships between the criteria.
Based on the original function of k-means and OWA algorithm used, it is
predicted that OWA-based k-means clustering (Cheng et al, 2009) works by
modifying some of its stages. In this study, it will be done by modification of
OWA-based k-means clustering (Cheng et al, 2009) and validated it in the
clustering of iris dataset. This research aims to apply OWA-based k-means
clustering in clustering iris data sets for validation and measure accuracy
rateof OWA-based k-means clustering in the iris data sets. Resultshowed that
accuracy of OWA-based k-means clustering in clustering iris data sets is
96.67%, which was better than k-means clustering method of 89.33%.
Penulis: Millatul Ulya
Millatul Ulya
Kode Jurnal: jppertaniandd110268
