ANALISIS PENYEBARAN KASUS COVID-19 MENGGUNAKAN GRAPH SIGNAL PROCESSING: STUDY KASUS DI KOTA KUPANG, INDONESIA
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Amin Ajaib Maggang(1*)
Universitas Nusa Cendana
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Sarlince O. Manu(2)
Universitas Nusa Cendana
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Beby H. A. Manafe(3)
Universitas Nusa Cendana
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Johanis F. M. Bowakh(4)
Universitas Nusa Cendana
(*) Corresponding Author
Abstract
To provide information on the spread of Covid-19 cases, the Kupang City government, East Nusa Tenggara province, has created a map of the spreading pattern of Covid-19 cases on the website of Kupang City. However, similar to most maps, it only provides information on the number of daily cases. Information such as a high-risk sub district or an outbreak sub-district has yet to be recorded on the web page. Therefore, this research aimed to analyse the spread of Covid-19 cases to obtain more critical information about its contagious pattern. This research used the Graph Signal Processing (GSP) techniques to analyse the spread of covid-19 cases with respect to the underlying graph structure of 51 sub-districts in Kupang City. Unlike other data analysis methods, GSP can process data by considering the relationship between objects, such as the distance between sub-districts. The data used in this research was the number of Covid-19 cases recorded in the sixth of March 2021. The results showed that GSP can capture the contagious pattern of Covid-19 cases in Kupang City by identifying sub-districts at risk of experiencing a spike in cases, such as the Nunleu sub-district, and the Airnona sub-district as the sources of outbreaks
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