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NI MADE SRI SUGIANTARI
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Mathematics

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PENERAPAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA KASUS PENYAKIT COVID-19 DI PROVINSI BALI NI LUH PUTU SUCIPTAWATI; NI MADE SRI SUGIANTARI; MADE SUSILAWATI
E-Jurnal Matematika Vol 12 No 1 (2023)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2023.v12.i01.p393

Abstract

COVID-19 has spread widely to all parts of the world, including Indonesia. Bali is included in the top ten with the highest number of COVID-19 cases in Indonesia. The spread of COVID-19 is thought to be influenced by various factors in each location that cause spatial heterogeneity. The method that can be used to analyze if there is spatial heterogeneity is Geographically Weighted Regression (GWR). This study aims to model the factors that influence the number of COVID-19 cases in Bali. The results showed that the GWR model with the adaptive kernel bisquare weighting function was more suitable to be used to model the number of COVID-19 cases in Bali because it had the largest value of 96.36%. The factors that influence the number of COVID-19 cases in Bali are population density and the population aged 20-44 years old.
Co-Authors Made Susilawati Ni Luh Putu Suciptawati