Categorical Data Clustering with K-Modes Method on Fire Cases in DKI Jakarta Province

Authors

  • Widia Handa Riska Universitas Negeri Padang
  • Dony Permana
  • Atus Amadi Putra
  • Zilrahmi

DOI:

https://doi.org/10.24036/ujsds/vol2-iss1/115

Keywords:

Categorical Data Clustering, Davies Bouldin Index, Fire Cases, K-Modes

Abstract

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.

Published

2024-02-25

How to Cite

Widia Handa Riska, Dony Permana, Atus Amadi Putra, & Zilrahmi. (2024). Categorical Data Clustering with K-Modes Method on Fire Cases in DKI Jakarta Province. UNP Journal of Statistics and Data Science, 2(1), 56–63. https://doi.org/10.24036/ujsds/vol2-iss1/115

Most read articles by the same author(s)

<< < 2 3 4 5 6 7