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Dengue Cases Prediction in Kupang
Abstract
The pandemic of coronavirus (COVID-19) causes another infectious disease such as dengue is neglected in Indonesia. Since the majority of resources, both human and capital, are focusing more on COVID-19, it is still essential to also manage dengue as it is still becoming a threat to the community. This study aims to predict the number of cases of dengue in Kupang, East Nusa Tenggara, Indonesia. This study area is in Kupang city, East Nusa Tenggara province, Indonesia. Data regarding monthly dengue reported cases by months from January 2010–December 2019 in Kupang city was collected to describe the temporal patterns of dengue cases. The Box-Jenkins approach is used to fit the auto-regressive integrated moving average (ARIMA) models. This model will predict monthly dengue cases for the year 2020 (12 months). Data analyzed using the Minitab program version 18.0. This study shows that seasonality was an essential component for Kupang city, which performed an exploratory analysis of dengue incidence (ln data) for 2010–2019. The linear trend model shows the prediction of dengue cases in 2020 was Yt=36.9−0.131 × t. The forecast tells that dengue will remain high for the whole year. Maintaining a clean environment, reduction of breeding sites, and other protective measurements against dengue transmission are significant to perform.
PREDIKSI KASUS DEMAM BERDARAH DENGUE DI KUPANG
Pandemi virus corona (COVID-19) mengakibatkan penyakit menular lain seperti dengue terbengkalai di Indonesia karena mayoritas sumber daya, baik manusia maupun permodalan, lebih berfokus pada COVID-19, sedangkan penanggulangan demam berdarah dengue (DBD) masih menjadi hal yang penting karena masih menjadi ancaman bagi masyarakat. Penelitian ini bertujuan memprediksi jumlah kasus DBD di Kupang, Nusa Tenggara Timur, Indonesia. Wilayah studi ini berada di Kota Kupang, Provinsi Nusa Tenggara Timur, Indonesia. Data bulanan kasus DBD yang dilaporkan per bulan dari Januari 2010–Desember 2019 di Kota Kupang dikumpulkan untuk menggambarkan pola temporal kasus DBD. Pendekatan Box-Jenkins digunakan untuk menyesuaikan model auto-regressive integrated moving average (ARIMA). Model ini akan memprediksi kasus DBD bulanan untuk tahun 2020 (12 bulan). Data dianalisis menggunakan program Minitab versi 18.0. Studi ini menunjukkan bahwa musim merupakan komponen penting bagi Kota Kupang yang melakukan analisis eksplorasi kejadian DBD (dalam data) untuk tahun 2010–2019. Model tren linier menunjukkan prediksi kasus DBD tahun 2020 adalah Yt=36.9−0.131 × t yang memperkirakan DBD akan tetap tinggi sepanjang tahun. Menjaga kebersihan lingkungan, mengurangi tempat berkembang biak, dan tindakan perlindungan lainnya terhadap penularan DBD penting dilakukan.
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DOI: https://doi.org/10.29313/gmhc.v8i3.6727
pISSN 2301-9123 | eISSN 2460-5441
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