用 K-Modes 方法对雅加达省火灾案例进行分类数据聚类

Widia Handa Riska, D. Permana, Atus Amadi Putra, dan Zilrahmi
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引用次数: 0

摘要

在雅加达省,火灾的数量每年都在增加和减少。因此,需要努力预防和减少火灾风险。BPBD DKI Jakarta 负责这方面的工作。然而,要使这些工作取得成效,需要了解经常发生的火灾模式。火灾模式可通过 K-Modes 分类聚类分析来了解。所使用的数据是 2018 年 DKI 雅加达的火灾数据。根据戴维斯-博尔丁指数(Davies Bouldin Index)值得出最佳聚类数为 6 个聚类,其中最小的 DBI 值为 6.22。在这 6 个聚类中,聚类 3 是火灾案例数量最多的聚类。第 3 聚类有一个中心点,即 11 月星期五在 Cakung 区发生的火灾案例是由于电路短路,烧毁了民房,很少造成轻伤、重伤或死亡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Categorical Data Clustering with K-Modes Method on Fire Cases in DKI Jakarta Province
In DKI Jakarta Province, the number of fires increases and decreases every year. For this reason, efforts need to be made to prevent and reduce the risk of fire. BPBD DKI Jakarta is responsible for this matter. However, for these efforts to be effective, information is needed regarding fire patterns that frequently occur. Fire patterns can be seen using K-Modes categorical clustering analysis. The data used is fire data in DKI Jakarta in 2018. The optimal number of clusters was obtained as 6 clusters based on the Davies Bouldin Index value with the smallest DBI value is 6,22. Of the six clusters, cluster 3 is the cluster with the highest number of fire cases. Cluster 3 has a centroid, namely that fire cases occurred on Friday, November, in Cakung District, due to an electrical short circuit, burning down residential houses and rarely causing minor injuries, serious injuries or deaths.
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