WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING
In this paper, it will be shown that data related to CoViD-19 in West Java Province can be segmented into several characteristics that can be used as an alternative in evaluating Government control of CoViD-19 transmission. Initially, the authors used principal component analysis to represent dat...
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id-itb.:520762021-02-02T09:10:14ZWEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING Arnandy, Jovi Indonesia Final Project Government intervention evaluation, CoViD-19 transmission, k?medoid clustering method, principal component analysis INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/52076 In this paper, it will be shown that data related to CoViD-19 in West Java Province can be segmented into several characteristics that can be used as an alternative in evaluating Government control of CoViD-19 transmission. Initially, the authors used principal component analysis to represent data in smaller subspaces for ease of visualization with optimal total projected variance of the data. After that, the authors utilized the k?medoid clustering method for the principal component analysis output segmentation. Finally, the results of the clustering are observed and analyzed as a first step in concluding the evaluation of Government control over CoViD-19 transmission. text |
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Institut Teknologi Bandung |
| building |
Institut Teknologi Bandung Library |
| continent |
Asia |
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Indonesia Indonesia |
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Indonesia |
| description |
In this paper, it will be shown that data related to CoViD-19 in West Java Province
can be segmented into several characteristics that can be used as an alternative in
evaluating Government control of CoViD-19 transmission. Initially, the authors
used principal component analysis to represent data in smaller subspaces for ease of
visualization with optimal total projected variance of the data. After that, the authors
utilized the k?medoid clustering method for the principal component analysis
output segmentation. Finally, the results of the clustering are observed and analyzed
as a first step in concluding the evaluation of Government control over CoViD-19
transmission. |
| format |
Final Project |
| author |
Arnandy, Jovi |
| spellingShingle |
Arnandy, Jovi WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| author_facet |
Arnandy, Jovi |
| author_sort |
Arnandy, Jovi |
| title |
WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| title_short |
WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| title_full |
WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| title_fullStr |
WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| title_full_unstemmed |
WEST JAVAâS COVID-19 RELATED DATA SEGMENTATION WITH PRINCIPAL COMPONENT ANALYSIS AND K-MEDOID CLUSTERING |
| title_sort |
west javaâs covid-19 related data segmentation with principal component analysis and k-medoid clustering |
| url |
https://digilib.itb.ac.id/gdl/view/52076 |
| _version_ |
1822001144017190912 |