Implementation of Ward AHC for Material Clustering Based on Mechanical Parameters - Yusuf, Edy; Bakhtiar; Syukriah; Burhanuddin; Riyadhul Fajri (Universitas Mulia, 2024)
This study aims to implement the Ward Agglomerative Hierarchical Clustering (Ward AHC) algorithm to classify materials based on mechanical parameters, including tensile strength (Su), yield strength (Sy), elastic modulus (E), shear modulus (G), Poisson's ratio (μ), and density (ρ). The clustering results reveal that the data is divided into three main groups with the following distributions: Cluster 1 (321 data points), Cluster 2 (403 data points), and Cluster 3 (828 data points). Each cluster exhibits unique characteristics: Cluster 1 is dominated by materials with low Su and Sy values, moderate E and G values, and light ρ. Cluster 2 features materials with very high E values, while Su, Sy, and G values vary. Cluster 3 is characterized by moderate Su values, low Sy values, high E and G values, and light ρ. An evaluation using the Silhouette Score yielded a value of 0.492, indicating that the clustering quality is reasonably good, though there is evidence that some data points may lie near the boundaries between clusters.