Pemodelan Matematika Penyebaran COVID-19: Studi Kasus Di Jawa Timur

Setiawati, Erna (2022) Pemodelan Matematika Penyebaran COVID-19: Studi Kasus Di Jawa Timur. Masters thesis, Institut Teknologi Sepuluh Nopember.

	Text 06111850012003-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 April 2024. Download (2MB) | Request a copy
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Abstract

COVID-19 adalah penyakit menular yang disebabkan oleh SARS-CoV-2. Sejak 30 Januari 2020 World Health Organization (WHO) menyatakan bahwa COVID-19 merupakan pandemi global. Di Indonesia, kasus ini mulai berkembang sejak akhir Februari 2020 dan hingga saat ini masih terus terjadi peningkatan infeksi baru. Beberapa model matematika dan prediksi kasus COVID-19 di Indonesia telah dilakukan, namun hasilnya belum sepenuhnya akurat. Hal ini mungkin disebabkan adanya pola yang berbeda-beda di setiap daerah. Pada penelitian ini dikonstruksi model matematika penyebaran COVID-19 di wilayah Jawa Timur. Pemodelan dilakukan berbasis model Susceptible-Vaccinated-Infected-Recovered-Death (SVIRD) yang parameter-parameternya dihitung berdasarkan data. Estimasi variabel dilakukan menggunakan metode Kalman Filter. Pada penelitian ini diperoleh hasil estimasi jumlah orang yang terinfeksi COVID-19, jumlah orang yang menerima vaksin dosis pertama, jumlah orang yang sembuh dari COVID-19 dan jumlah orang yang menerima vaksin dosis kedua, dan jumlah orang yang meninggal karena COVID-19 mendekati nilai aktualnya, yaitu data kumulatif harian kasus COVID-19 dan data kumulatif harian pelaksanaan vaksinasi dosis pertama dan vaksinasi dosis kedua di provinsi Jawa Timur dari tanggal 23 Februari 2021 sampai 22 Juni 2021 dengan masing-masing nilai MAPE 0,00097%, 0,00202%, 0,00147%, dan 0,09881% sehingga nilai estimasinya dapat dikatakan memiliki akurasi peramalan yang tinggi, sehingga dari hasil estimasi variabel yang diamati dapat digunakan untuk memprediksi jumlah kasus COVID-19 di Jawa Timur. Selain itu, diperoleh nilai bilangan reproduksi dasar R0 = 1,1086 > 0. Hal ini menunjukkan bahwa COVID-19 akan terus ada dalam populasi. Oleh karena itu dilakukan analisis sensitivitas parameter terhadap bilangan reproduksi dasar (R0) dan diperoleh kesimpulan bahwa parameter yang paling sensitif terhadap perubahan nilai R0 adalah tingkat infeksi (β) dan proporsi orang yang divaksin dua kali (ω).
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COVID-19 is an infectious disease caused by SARS-CoV-2. Since 30 January 2020 the World Health Organization (WHO) declared COVID-19 as a global pandemic. In Indonesia, this case begin to develop since the end of February 2020 and until now there is still an increase in new infections. Several mathematical models and predictions of COVID-19 cases in Indonesia have been conducted, but the results are not fully accurate. This may be due to different patterns in each region. In this study, a mathematical model of the spread of COVID-19 is constructed in East Java. Modeling is done based on the Susceptible-Vaccinated-Infected-Recovered-Death (SVIRD) model which parameters are calculated based on the data. Variable estimation is carried out using the Kalman Filter method. In this study, the estimation results of the number of people infected with COVID-19, the number of people who received the first dose of vaccine, the number of people who recovered from COVID-19 and the number of people who received the second dose of vaccine, and the number of people who died from COVID-19 are close to the actual value, namely daily cumulative data of COVID-19 cases and daily cumulative data of the implementation of the first dose of vaccination and the second dose of vaccination in East Java province from 23 February 2021 to 22 June 2021 with each MAPE value of 0.00097%, 0.00202%, 0.00147%, and 0.09881% so that the estimated value can be said to have a high forecasting accuracy, so the estimation results of the observed variables can be used to predict the number of COVID-19 cases in East Java. In addition, the basic reproduction number value is R0 = 1.1086 > 0. This indicates that COVID-19 will continue to exist in the population. Therefore, a parameter sensitivity analysis is carried out on the basic reproduction number (R0) and it is concluded that the most sensitive parameters to changes in the value of R0 are the infection rate (β) and the proportion of people who are vaccinated twice (ω).

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	COVID-19, SVIRD model, basic reproduction number, kalman filter, sensitivity analysis, model SVIRD, bilangan reproduksi dasar, analisis sensitifitas
Subjects:	Q Science > QA Mathematics > QA401 Mathematical models. Q Science > QA Mathematics > QA402 System analysis. Q Science > QA Mathematics > QA402.3 Kalman filtering.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44101-(S2) Master Thesis
Depositing User:	Erna Setiawati
Date Deposited:	09 Feb 2022 02:12
Last Modified:	09 Feb 2022 02:12
URI:	http://repository.its.ac.id/id/eprint/93289

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