Studi Simulasi Model SIR Pada Data Covid-19 Di Jawa Timur Serta Analisis Dampak Pandemi Pada Sektor Transportasi Di Indonesia Dengan Metode Regresi Time Series Dan ARIMA

Mashita, Adilya Rizki (2021) Studi Simulasi Model SIR Pada Data Covid-19 Di Jawa Timur Serta Analisis Dampak Pandemi Pada Sektor Transportasi Di Indonesia Dengan Metode Regresi Time Series Dan ARIMA. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

	Text Laporan TA-06211740000089-Adilya Rizki M-ANDEF-PW124.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (1MB) | Request a copy
	Text Laporan TA-06211740000089-Adilya Rizki M-ANDEF-PW124.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (1MB) | Request a copy

Abstract

Dari hasil estimasi pemodelan SIR data Covid-19 di Jawa Timur pada periode awal, kedua dan ketiga, dan setelah di optimasi dengan mengunakan Genetic Algorithm, telah didapatkan nilai parameter pada periode awal β = 0,018 dan γ = 7, pada periode kedua β = 0,017 dan γ = 6,8 dan pada periode ketiga (satu tahun) β = 0,015 dan γ = 7,3. Nilai parameter yang dihasilkan tersebut yang telah optimum, sehingga grafik model SIR kurva infected kenaikan atau individu yang terinfeksi yang dihasilkan cukup sama dengan data aktual. Pada grafik SIR hasil forecasting dengan periode 3 bulan dan 6 bulan, sudah sesuai dengan hasil dari studi terapan. Dari grafik studi simulasi didapatkan forecasting Covid-19 akan berakhir pada tanggal 6 Juni 2037. Dampak pandemi Covid-19 juga mempengaruhi jumlah transportasi yang ada di Indonesia. Dihasilkan hasil dari forecasting yang dibandingkan dengan data data jumlah penumpang kereta hasil terbaik didapatkan dari model model ARIMA Sehingga pada peramalan terbaik jumlah penumpang kapal dan pesawat didapatkan dari model regresi time series.
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From the estimation results of SIR modeling of Covid-19 data in East Java
in the initial, second and third periods, and after optimization using
Genetic Algorithm, the parameter values in the initial period = 0.018 and
= 7, in the second period = 0.017 and = 6.8 and in the third period (one
year) = 0.015 and = 7.3. The resulting parameter values are already
optimum, so the graph of the SIR curve of infected increases or infected
individuals produced is quite the same as the actual data. In the SIR
graph, the forecasting results for a period of 3 months and 6 months are
in accordance with the results of applied studies. From the graph of the
simulation study, it is found that the forecasting of Covid-19 will end on
June 6, 2037. The impact of the Covid-19 pandemic also affects the
amount of transportation in Indonesia. The results from forecasting are
compared with data on the number of train passengers, the best results
are obtained from the ARIMA model

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Covid-19, Genetic Algorithm, Regresi Time Series, Time Series Regression, SIR
Subjects:	R Medicine > RA Public aspects of medicine > RA644.C67 COVID-19 (Disease)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Adilya Rizki Mashita
Date Deposited:	23 Sep 2021 01:28
Last Modified:	23 Sep 2021 01:28
URI:	http://repository.its.ac.id/id/eprint/92027

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