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All Journal Mulia International Journal in Science and Technical Journal of Computer System and Informatics (JoSYC) Jurnal Tika KLIK: Kajian Ilmiah Informatika dan Komputer Multica Science and Technology AJAD : Jurnal Pengabdian kepada Masyarakat Sisfo: Jurnal Ilmiah Sistem Informasi Data Sciences Indonesia (DSI) Aceh Journal of Community Engagement (AJCE) Lentera Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Riyadhul Fajri
Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Almuslim, Bireuen - Aceh
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Physics Social Sciences

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Journal : Multica Science and Technology

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Implementation of Ward AHC for Material Clustering Based on Mechanical Parameters Yusuf, Edy; Bakhtiar; Syukriah; Burhanuddin; Riyadhul Fajri
Multica Science and Technology Vol 4 No 2 (2024): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v4i2.977

Abstract

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.
Co-Authors Aflizar Aflizar Amanda, Putri Andre Maireza Asmawi Bakhtiar Burhanuddin Burhanuddin Burhanuddin Dedy Armiady Erfan Syah, Muhammad Fadillah, Tengku Farhan Farizal Fathia Firzha Fitria Hannan Asrawi Heri Gustami Intan Arianti Iqbal Iqbal Iqbal Ibal Irma Ayuni izky, Alfaroel Juandana, Rio Adian M. Saleh Mira Nataturi Muhammad Rizal Munar Musrizal, Musrizal Mutammimul Ula Raudhatul Jannah Rekha Audina REZA PAHLEVI Richki Hardi Salamah Saptari, Mochamad Ari Sri Winar Sriwinar Sriwinar Sriwinar, Sriwinar Sulaiman, Munawar Syukriah Teuku Muhammad Johan Ulfa M. , Mahdalena Vianaza, Vianaza Yella Cinni Ujung Yusuf, Edy Zulkifli Zulkifli Zulkifli Zulkifli Zulkifli