Cityplan and Urban & Regional Planning ITB worked together for healthy city research. This research focuses on how we can solve COVID-19 problems through policy recommendations with paper policy. This research focuses on Jakarta City.
Qualitative research focuses on content analysis in the public policy document and several articles or publications.
Quantitative research focuses on using spatial data of the physical environment and people’s opinions on social-economic behavior throughout the pandemic.
Correlation Analysis between DKI Jakarta's COVID-19 Policies and Rate of COVID-19 increases and distribution
In this process, we want to discover the relation between COVID-19 policies and their impact on how many COVID-19 cases are in Jakarta.
Spatial Correlation Analysis on COVID-19 Cases Distribution
This analysis contains three main processes, data training, spatial autocorrelation & hotspot analysis, and spatial modeling.
In this phase, we collect, cleanse, and transform primary data from the questioner to spatial form. We also do a transformation for secondary data.
Spatial Autocorrelation & Hotspot Analysis
Spatial autocorrelation analysis focuses on evaluating the spatial pattern that will be formed in clustered, dispersed, or random patterns. Also, hotspot analysis focus on identification spatial classes from cold spots to hot spots.
Spatial modeling used two main methods, Ordinary Least Square and Geographically Weighted Regression. This process has an output in the form of a model of correlation between every spatial variable and COVID-19 zones.