UNP Journal of Statistics and Data Science
Vol. 2 No. 1 (2024): UNP Journal of Statistics and Data Science

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

Widia Handa Riska (Universitas Negeri Padang)
Dony Permana (Unknown)
Atus Amadi Putra (Unknown)
Zilrahmi (Unknown)



Article Info

Publish Date
25 Feb 2024

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.

Copyrights © 2024






Journal Info

Abbrev

ujsds

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

Description

UNP Journal of Statistics and Data Science is an open access journal (e-journal) launched in 2022 by Department of Statistics, Faculty of Science and Mathematics, Universitas Negeri Padang. UJSDS publishes scientific articles on various aspects related to Statistics, Data Science, and its ...