Rafflesia, Ulfasari and Rosadi, Dedi (2023) The application of K-means clustering and fuzzy C-means clustering analysis for modeling the spread of second wave coronavirus disease in Indonesia. In: 3rd International Seminar on Science and Technology: Science, Technology and Data Analysis for Sustainable Future, ISSTEC 2021, 30 November 2021, Yogyakarta.
Full text not available from this repository. (Request a copy)Abstract
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. To prevent and slow down the transmission of this disease requires a clear information about the virus itself, the disease it causes, and how it is spread. This paper presents the application of k-means and fuzzy c-means clustering analysis to show the cluster of the spread of second-wave coronavirus disease in Indonesia. The variables considered in this study are the number of confirmed COVID-19 positive, the number of patients, the number of deaths and the number of recovered patients, using data at May 31st 2021. Based on the SSE (Sum Square Error), Silhouette index and Gap Statistics, it is founded that the best clustering is using 2 clusters
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Library Dosen |
Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Mathematics and Natural Sciences > Mathematics Department |
Depositing User: | Masrumi Fathurrohmah |
Date Deposited: | 26 Jun 2024 06:52 |
Last Modified: | 26 Jun 2024 06:52 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/2450 |