Distance Analysis Measuring for Clustering using K-Means and Davies Bouldin Index Algorithm
نویسندگان
چکیده
The purpose of this research is to analyze mapping results in the form clusters formed using clustering method measures. This done determine connections that existing create. Some measurements used are mixed measurements, Bregman differences, and number (Mixed Euclidean Distance, Generalized Divergence, Squared Mahalanobis Distance). Distance measurement shall be applied on with primary school facilities Indonesia. Davies Bouldin Index (DBI) different from cluster test (k = 2-10) for each Measure. average DBI value type measure (mixed measure) numerical Distance) 0.54. (Bregman divergences) numeric (generalized IDivergence) 0.66. 0.77 (Squared From results, distance 2), namely 0.269, have best value.
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ژورنال
عنوان ژورنال: TEM Journal
سال: 2022
ISSN: ['2217-8333', '2217-8309']
DOI: https://doi.org/10.18421/tem114-55