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Sisca Indah Pratiwi
Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro
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ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018) Sisca Indah Pratiwi; Tatik Widiharih; Arief Rachman Hakim
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.8.4.486-495

Abstract

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient
Co-Authors Arief Rachman Hakim Tatik Widiharih