Amalia MS, Karohmatul (2021) Estimasi Parameter Model Penyebaran COVID-19 Dan Model Arus Kas Regime-Switching Dengan Metode Random Search Guna Mengoptimalkan Arus Kas Perusahaan. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pandemi COVID-19 berdampak serius pada sektor ekonomi
suatu perusahaan. Sebagian besar perusahaan mengalami penurunan kinerja, penurunan harga saham, dan masalah serius lainnya. Untuk mengatasi hal tersebut, perusahaan melakukan strategi berupa sistem pergantian keadaan perusahaan aktif atau tidak aktif sementara untuk memaksimumkan pendapatan perusahaan serta dapat mengendalikan kasus infeksi COVID-19 di perusahaannya.
Dalam Tugas Akhir ini, dimodelkan penyebaran COVID-19 di Jawa Timur dengan tiga model modifikasi SIRD stokastik untuk dapat memproyeksi penyebaran COVID-19 sebuah perusahaan besar di Jawa Timur. Hasil estimasi parameter terbaik menggunakan metode random search dengan 1.000.000 iterasi ditunjukkan oleh model modifikasi SIRD stokastik 1 dengan independen Brownian motion pada setiap kompartemennya, yang menghasilkan rata-rata nilai
MAPE terkecil yaitu sebesar 30,2521%. Beberapa upaya dilakukan untuk memperbaiki rata-rata nilai MAPE tersebut. Upaya yang menghasilkan rata-rata nilai MAPE terbaik sebesar 3,1699% adalah optimalisasi tiap titik. Oleh karena itu, simulasi arus kas regime-switching dilakukan menggunakan model modifikasi SIRD stokastik 1 dengan nilai parameter yang dihasilkan dari optimalisasi
tiap titik untuk menentukan ambang batas pergantian keadaan perusahaan besar di Jawa Timur yang jumlah total karyawannya sebanyak 1.000. Hasil simulasi arus kas regime-switching adalah diperoleh ambang batas pergantian keadaan yaitu IH sebesar 3,0% dan IL sebesar 1,5% dengan nilai maksimum pendapatannya mencapai Rp 463.858.768,-. Hasil tersebut menunjukkan bahwa perusahaan akan menerapkan keadaan tidak aktif sementara ketika karyawan yang terinfeksi lebih dari 30 orang dan perusahaan dapat
aktif kembali ketika karyawan yang terinfeksi kurang dari 15 orang.
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The COVID-19 pandemic has a serious impact on the economic sector of a company. Most companies experience declining performance, falling stock prices, and other serious problems. To overcome this, the company carried out a strategy in the form of a system of changing the state of the company being active or temporarily inactive to maximize the company’s revenue and be able to control cases of COVID-19 infection in the company. In this
Final Project, the spread of COVID-19 in East Java is modeled with three modified stochastic SIRD models to be able to project the spread of COVID-19 in a large company in East Java. The best parameter estimation results using the random search method with 1,000,000 iterations are shown by a modified SIRD stochastic model 1 with independent Brownian motion in each compartment, which produces the smallest average MAPE value of 30.2521%.
Several attempts were made to improve the average MAPE score. The effort that produces the best average MAPE value of 3.1699% is the optimization of each point. Therefore, the simulation of cash flow regime-switching was carried out using a modified SIRD stochastic model 1 with parameter values generated from the optimization of each point to determine the threshold for changing the state of large companies in East Java with a total number of employees of 1,000. The result of the simulation of cash flow regime-switching is that the threshold for the change of state is IH of 3.0% and IL of 1.5% with the maximum value of income reaching Rp. 463,858,768,-. These results indicate that the company will apply a temporary inactive state when the infected employee is more than 30 people and the company can reactivate when the infected employee is less than 15 people.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Brownian motion, SIRD, stochastic, random search, regime-switching,Brownian motion, SIRD, stokastik, random search, regime-switching. |
| Subjects: | H Social Sciences > HA Statistics > HA31.7 Estimation R Medicine > RA Public aspects of medicine > RA644.C67 COVID-19 (Disease) |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Karohmatul Amalia MS |
| Date Deposited: | 26 Aug 2021 14:07 |
| Last Modified: | 26 Aug 2021 14:07 |
| URI: | http://repository.its.ac.id/id/eprint/90654 |
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