UTILIZATION OF MEAN SPATIAL STATISTIC AND CLUSTER AND OUTLIER ANALYSIS METHOD IN IDENTIFYING THE SPREAD PATTERNS OF COVID-19: JAKARTA 2021
<p align="justify"> Studying the spread of COVID-19 cases in a specific region requires the integration of spatial and statistical analyses as essential considerations for understanding the patterns and dynamics of the virus transmission. This research aims to conduct spatial and...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/75093 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | <p align="justify"> Studying the spread of COVID-19 cases in a specific region requires the integration
of spatial and statistical analyses as essential considerations for understanding the
patterns and dynamics of the virus transmission. This research aims to conduct
spatial and statistical analysis to uncover spatial patterns, clustering tendencies, and
the shifting mean center of COVID-19 cases using Spatial Autocorrelation (Moran's
I), Cluster and Outlier Analysis (Anselin Local Moran's I), and Mean Spatial
Statistic methods. The analysis utilizes cumulative and pertambahan data of positive
COVID-19 patients, recovered patients, and fatalities in DKI Jakarta, based on
official government records. The findings reveal the identification of spatial patterns,
clustering tendencies, and the shifting mean center of COVID-19 cases.
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