PREDIKSI JUMLAH KASUS BARU COVID-19 DI INDONESIA DENGAN FUZZY TIME SERIES MODEL CHEN

PUSPITA, WIWIK ANUM and Utami, Alvi Syahrini and Miraswan, Kanda Januar (2021) PREDIKSI JUMLAH KASUS BARU COVID-19 DI INDONESIA DENGAN FUZZY TIME SERIES MODEL CHEN. Undergraduate thesis, Sriwijaya University.

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Abstract

Coronavirus Diseases 2019 (Covid-19) is a disease caused by a virus that originated in Wuhan, China. This virus infects people rapidly to the country of Indonesia. According to the latest Covid-19 Development Team in Indonesia, as of 09/08/2021, there were around 3,686,740 people who were confirmed positive for Covid-19. With the numbers continuing to grow, predictions of new cases of Covid-19 in Indonesia were made using the time series method. The method used by the researcher is Chen's Fuzzy Time Series. The purpose of the researcher is to forecast, to find out the prediction of the number of new cases of Covid -19 in Indonesia using the FTS Chen method into software. In addition, in order to provide information to predict, so that the government knows and can make decisions. To measure the performance of the method, the Mean Absolute Percentage Error (MAPE) is used as a measure of the level of accuracy of the forecasting performed. The test data used were 363 data with several variations of parameters D_1 and D_2. From the results of the analysis that was tested by the researcher, with 50 trials of parameter input, better accuracy results were obtained at input D_1 = 135135 and D_(2 )= 2000 with MAPE = 35.55006797%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Number of new cases, Covid-19, Fuzzy Time Series Chen, MAPE
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > T Technology (General) > T58.4 Managerial control systems Information technology. Information systems (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Wiwik Anum Puspita
Date Deposited:	11 Jan 2022 07:43
Last Modified:	11 Jan 2022 07:43
URI:	http://repository.unsri.ac.id/id/eprint/61091

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