Mapping the Poverty incidence in Bali, Indonesia and its Determinants using GIS
Channel: Katina Michael
Date: 2021-01-01

A paper submitted to IEEE ISTAS20 by UOW's Ni Putu Intan Maharani on Mapping the Poverty Incidence in Bali, Indonesia and its Determinants using Geographic Information Systems (GIS). Recorded on 15 August 2020. Project conducted using open source QGIS.

In this paper, poverty incidence causes in Bali, Indonesia is analyzed, and the visualization of the poverty data and its determinants are generated. Regression slope test is used to determine whether the chosen independent variables as potential poverty determinants has a statistically significant association with the poverty incidence in which is executed in R software. The correlation coefficient of each potential poverty determinant with the poverty incidence also calculated using R software to see the direction of the association (positive or negative). QGIS software is used to visualize the data into a map. This will enable the easy understanding of the data and to detect pattern or trends of the data easily. 

From the regression slope test, it is found that human development index, average duration of attending school, university enrolment ratio, literacy rate, GRDP and number of hotels have significant association with the poverty incidence at 5% significant level. The thematic maps of poor people percentage by regency/municipality and the significantly associated variables are generated as the visualization of data by using QGIS software in which the join between the map data (base map) and the tabular data is conducted. Spatial vector layers such as points and lines are also analyzed in relation with poverty incidence. The satellite image of Bali is also presented to see the general overview of Bali island from the above.

In conclusion, poverty reduction strategies can be enhanced by also focusing on the significantly associated variables/factors and the visualization of poverty related data is useful to easily discover the pattern or trends of the data.