PEMODELAN KASUS COVID-19 DI INDONESIA MENGGUNAKAN ANALISIS SPASIAL DENGAN PENDEKATAN BAYESIAN
Abstract
Kasus terkonfirmasi positif Covid-19 dilaporkan pertama kali di Indonesia pada tanggal 2 Maret 2020. Hingga 30 September 2022, Indonesia memiliki 6.465.207 kasus. Berbagai penelitian mengenai pemodelan kasus Covid-19 telah dilakukan. Akan tetapi, penelitian menggunakan model Bayesian spasial Conditional Autoregressive (CAR) Leroux (BSCL) untuk kasus Covid-19 di 34 provinsi di Indonesia belum sepenuhnya dilakukan. Penelitian ini bertujuan untuk mendapatkan model BSCL terbaik dalam mengestimasi risiko relatif (RR) kasus Covid-19 di 34 provinsi di Indonesia dan menghasilkan peta tematik RR. Data agregat kasus positif Covid-19 (2 Maret 2020-30 September 2022) digunakan dalam penelitian ini. Selain itu, data jumlah penduduk di 34 provinsi di Indonesia tahun 2021 juga digunakan. Kriteria dalam memilih model terbaik adalah dengan melihat nilai residual dari Modifikasi Moran’s I (MMI) yang lebih dekat ke nol, nilai Watanabe Akaike Information Criteria yang terkecil serta nilai Deviance Information Criteria (DIC) terkecil. Hasil pengolahan data Covid-19 menunjukkan bahwa model BSCL dengan hyperprior IG (0,1;0,1). merupakan model terbaik dalam mengestimasi RR kasus Covid-19 di Indonesia. Sekitar 29,41% (10 provinsi) di Indonesia yang memiliki nilai RR kategori tinggi terjangkit Covid-19. Provinsi dengan RR tertinggi dan terendah masing-masing adalah Provinsi DKI Jakarta (RR=5,68) dan Provinsi Nusa Tenggara Barat (RR=0,28).
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