Application of Cluster Analysis Using Agglomerative Method - Muhammad Rais Ridwan; Heri Retnawati (Numerical: Jurnal Matematika dan Pendidikan Matematika, 2021)
Improving the quality of human resources is the main supporting factor in increasing national productivity in various fields and development sectors. The government's productive investment activities that spur the nation's competitiveness in the global era prioritize Indonesia's education development. This study aims to cluster provinces in Indonesia based on educational indicators using the Agglomerative method consisting of the Average Linkage and Ward methods. Data collection is based on documentation techniques obtained from Statistics Indonesia in 2018. Data analysis used hierarchical cluster analysis consisting of data standardization, determining the size of the similarity or dissimilarity between data, the clustering process with a distance matrix, and seeing the characteristics of the cluster results formed. The second clustering method is by doing the initial grouping and determining the excellent cluster based on the average standard deviation ratio to the standard deviation between groups. Clustering results show the Ward method with the number of collections as many as 4 clusters and produces a ratio with a value of 0.01 smaller than the Average Linkage method. It shows that the cluster analysis method using the Ward method has better group accuracy quality than the Average Linkage method.