Parameter: Journal of Statistics
Vol. 3 No. 1 (2023)

APPLICATION OF TIME SERIES CLUSTER ANALYSIS IN CLUSTERING THE CENTRAL JAVA PROVINCE BASED ON THE POVERTY DEPTH INDEX

Dien Rizqiana, Zulfanita (Unknown)



Article Info

Publish Date
30 Jun 2023

Abstract

Poverty is a problem that continues to be faced, especially in developing countries such as Indonesia. Poverty is included in one of the Sustainable Development Goals (SDGs) programs, which is related to hunger and health. The time series data can be clustered based on the characteristics of the time series data and adjusted to the time series pattern. The choice of distance and method used must be adjusted to the dynamic structure of time series data. The purpose of this research is to cluster districts/cities in Central Java Province based on the poverty depth index value from 2017 to 2022. The variable that used in this research is the Poverty Depth Index of 35 districts in Central Java Province from 2017 to 2022. This research used cluster time series with DTW similarity measurment. Based on theDTW and cophenetic coefficient correlation value using three linkage methods, the average linkage method has the highest cophenetic coefficient correlation value of 0.8017988. Testing the quality of clusters using the silhouette coefficient using DTW distance and average linkage method and 2 clusters are included in the good cluster category with a silhouette coefficient value of 0.60. The resulting clusters using the DTW distance and average linkage method are cluster 1 consisting of 25 districts / cities and cluster 2 consisting of 10 districts.

Copyrights © 2023






Journal Info

Abbrev

parameter

Publisher

Subject

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

Description

Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its ...