BibTex Citation Data :
@article{J.Gauss33999, author = {Nor Hamidah and Rukun Santoso and Agus Rusgiyono}, title = {KLASTERISASI PROVINSI DI INDONESIA BERDASARKAN FAKTOR PENYEBARAN COVID-19 MENGGUNAKAN MODEL-BASED CLUSTERING t-MULTIVARIAT}, journal = {Jurnal Gaussian}, volume = {11}, number = {1}, year = {2022}, keywords = {Covid-19, Clustering, Model-Based Clustering t-Multivariat}, abstract = { The spread of Covid-19 had a significant impact in all sectors. Enforcement policies from the government that are appropriate with the conditions for the spread of the virus that are needed to prevent a bigger impact. Clusteritation by province based on data on the spread of Covid-19 is important for the government to set appropriate policies in order to prevent the spread of Covid-19. The data used include data on population density, testing rate, proportion of population 50 years and over, and proportion of population diligently hand-washing in each province. The data factors for the spread of Covid-19 tend to overlap and there are outliers in the data which causes the data not normally distributed. In this study, Model-Based Clustering t -multivariate was used for data clustering. The results show that using Integrated Completed Likelihood, two groups of optimal cluster were obtained. The second cluster has a higher risk of spreading Covid-19 than the first cluster. Keywords : Covid-19, Clustering, Model-Based Clustering t- Multivariat }, issn = {2339-2541}, pages = {56--66} doi = {10.14710/j.gauss.v11i1.33999}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/33999} }
Refworks Citation Data :
The spread of Covid-19 had a significant impact in all sectors. Enforcement policies from the government that are appropriate with the conditions for the spread of the virus that are needed to prevent a bigger impact. Clusteritation by province based on data on the spread of Covid-19 is important for the government to set appropriate policies in order to prevent the spread of Covid-19. The data used include data on population density, testing rate, proportion of population 50 years and over, and proportion of population diligently hand-washing in each province. The data factors for the spread of Covid-19 tend to overlap and there are outliers in the data which causes the data not normally distributed. In this study, Model-Based Clustering t-multivariate was used for data clustering. The results show that using Integrated Completed Likelihood, two groups of optimal cluster were obtained. The second cluster has a higher risk of spreading Covid-19 than the first cluster.
Keywords : Covid-19, Clustering, Model-Based Clustering t-Multivariat
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