K-Mean Clustering and Linear Regression Model for Grouping and Treatment Prediction on Natural Disasters and Poverty Average Percentage to Decrease the Victims in 2015 – 2019

  • Bambang Suharjo

Abstract

Indonesia as an archipelagic country prone to storms and tsunamis, a country that is a meeting between three active tectonic plates that are prone to earthquakes and volcanoes, as a country in the tropics that is raw against floods and landslides. Various studies have been conducted to examine the natural disasters and poverty and the many victims that arise.  Clustering is needed to be done to investigate the number of natural disasters, poverty and disaster victims so that they can be identified in each group and expected to make it easier to map and contribute to efforts to suppress victims and at the same time improve welfare.  And then, regression analysis is also needed to make sure the prediction about number of disasters influence poverty and victims. The best cluster was three cluster and the regression analysis give the recommendation that number of disasters influence poverty and victims.  Poverty also influence the victims.  So, we recommended to develop human resources and their wealth to reduce victims when the disasters happen.  

 

Keywords: natural disaster, poverty, victims, cluster, regression

Published
2020-06-06
How to Cite
Bambang Suharjo. (2020). K-Mean Clustering and Linear Regression Model for Grouping and Treatment Prediction on Natural Disasters and Poverty Average Percentage to Decrease the Victims in 2015 – 2019. International Journal of Advanced Science and Technology, 29(08), 4932-4941. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/26825
Section
Articles