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Related Experiment Video

Updated: Oct 7, 2025

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents

A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents

Published on: July 10, 2017

Revisiting social vulnerability analysis in Indonesia data.

Robert Kurniawan¹, Bahrul Ilmi Nasution², Neli Agustina³

¹Department of Statistical Computing, Polytechnic Statistics STIS, Jakarta 13330, Indonesia.

|January 10, 2022

Summary

This summary is machine-generated.

This study introduces a new dataset on social vulnerability in Indonesia, crucial for disaster management. The data, derived from the 2017 National Socioeconomic Survey, enables advanced spatial analysis of community resilience.

Keywords:

Disaster management Disaster mitigation Fuzzy geographically weighted clustering Multistage sampling Social vulnerability

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Area of Science:

Social Science
Disaster Management
Geographic Information Systems (GIS)

Background:

Social vulnerability is a key factor in disaster impact and recovery.
Indonesia faces significant disaster risks, necessitating robust vulnerability assessments.
Existing datasets may lack the granularity or specific dimensions required for detailed spatial analysis.

Purpose of the Study:

To present a comprehensive dataset on social vulnerability in Indonesia.
To provide data suitable for spatial analysis and disaster management planning.
To facilitate further research on social vulnerability and community resilience.

Main Methods:

Data compiled from the 2017 National Socioeconomic Survey (SUSENAS) and 2017 Population projection by BPS-Statistics Indonesia.
Utilized multistage sampling weights for accurate estimations.
Incorporated a distance matrix and population data for Fuzzy Geographically Weighted Clustering (FGWC).

Main Results:

A detailed dataset on social vulnerability dimensions is now available.
The dataset includes population data and growth information.
Supplementary distance matrix provided for advanced clustering techniques.

Conclusions:

The presented dataset is a valuable resource for understanding and addressing social vulnerability in Indonesia.
This data can significantly enhance disaster management strategies through spatial analysis.
Further research utilizing this dataset can lead to more targeted interventions and improved community resilience.