ABSTRACT
The objective of this study is to compare the different methods which are effective in predicting data of the short-term effect of COVID-19 confirmed cases and DJI closed stock market in the US. Data for confirmed cases of COVID-19 has been obtained from Worldometer, the database of Johns Hopkins University and the US stock market data (DJI) was obtained from Yahoo Finance. The data starts from 20 January 2020 (first confirmed COVID-19 case the US) to 06 December 2020 and DJI data covers 21 January 2019 to 04 December 2020. COVID-19 data was tested for the period 30 November to 06 December and DJI from 25 November 2020 to 04 December. From the result, we find that the method SutteARIMA was found more suitable to calculate the daily forecasts of COVID-29 confirmed cases and DJI in the US and this method has been used in this study. For the evaluation of the prediction methods, the accuracy measure means absolute percentage error (MAPE) has been used. The MAPE value with the SutteARIMA of 0.56 and 0.60 for COVID-19 and DJI stock respectively was found to be smaller than the MAPE value with ARIMA method.
ABSTRACT
The aim of this study is to predict 200.000 cases of COVID-19 in Spain. COVID-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 –17 April 2020. The data from 01 March 2020 –10 April 2020 used to fit with data from 11 April –17 April 2020. For the evaluation of the forecasting accuracy measures, we use mean absolute percentage error (MAPE). Based on the results of Sutter ARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 -17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.
ABSTRACT
This research was conducted to identify and describe the profile of publications in Indonesia in 2020. This research used the bibliometric methods. The data in this research were collected by searching through the Scopus database with the keywords: AFFILCOUNTRY "Indonesia" and PUBYEAR "2020" with the exception of AFFILCOUNTRY other than "Indonesia". Data were then analyzed based on author affiliation, subject, document type, source type, source title, and language. The results of the research indicated that the development of Indonesian scientific publications was dominated by article types (50.69%) and conference papers (45.83%) with the subject area of publication dominated by engineering, applied sciences, and social sciences as well as source titles from IOP and AIP. The highest contributing institutions for publication are Universitas Indonesia, Universitas Airlangga, Universitas Gadjah Mada, Hasanuddin University, Institut Teknologi Bandung, Universitas Diponegoro, IPB University, Universitas Sumatera Utara, Brawijaya University, and Universitas Sebelas Maret.
ABSTRACT
This study was conducted with the aim to the clustering of provinces in Indonesia of the risk of the COVID-19 pandemic based on coronavirus disease 2019 (COVID-19) data. This clustering was based on the data obtained from the Indonesian COVID-19 Task Force (SATGAS COVID-19) on 19 April 2020. Provinces in Indonesia were grouped based on the data of confirmed, death, and recovered cases of COVID-19. This was performed using the K-Means Clustering method. Clustering generated 3 provincial groups. The results of the provincial clustering are expected to provide input to the government in making policies related to restrictions on community activities or other policies in overcoming the spread of COVID-19. Provincial Clustering based on the COVID-19 cases in Indonesia is an attempt to determine the closeness or similarity of a province based on confirmed, recovered, and death cases. Based on the results of this study, there are 3 clusters of provinces.
ABSTRACT
Objectives Examining about forecasting the number of Covid-19 cases in the US can provide an overview and projection of the development of Covid-19 cases in the US so that policy makers can determine the steps that must be taken. The aim of this study was to seen whether Covid-19 confirmed cases in the US would reach 3 million cases with the SutteARIMA method forecasting approach. Methods Data from this study were obtained from the Worldometer 15 February 2020 – 2 July 2020. Data from 15 February 2020 – 25 June 2020 was used to do data fitting (26 June 2020 – 2 July 2020). Data fitting is used to see the extent of the accuracy of the SutteARIMA method in predicting data. To see the level of data accuracy, the MAPE method is used. Results The results of forecasting data fitting on 26 June 2020 – 2 July 2020: 2544732;2590888;2632477;2671055;2711798;2755128;2803729. The accuracy of SutteARIMA for the period 26 June 2020 – 2 July 2020 based on MAPE is 0.539% and forecasting results to obtain as many as 3 million confirmed cases, namely from from 05 – 06 June 2020: 1981299;2005706;2030283;2055031. Conclusions The SutteARIMA method predicts that 2 million confirmed cases of Covid-19 will be obtained on the WHO situation report day 168-170 or 05 – 07 June 2020.
ABSTRACT
This study aimed to predict the short-term of confirmed cases of covid-19 and IBEX in Spain by using SutteARIMA method. Confirmed data of Covid-19 in Spanish was obtained from Worldometer and Spain Stock Market data (IBEX 35) was data obtained from Yahoo Finance. Data started from 12 February 2020-09 April 2020 (the date on Covid-19 was detected in Spain). The data from 12 February 2020-02 April 2020 using to fitting with data from 03 April 2020 - 09 April 2020. Based on the fitting data, we can conducted short-term forecast for 3 future period (10 April 2020 - 12 April 2020 for Covid-19 and 14 April 2020 - 16 April 2020 for IBEX). In this study, the SutteARIMA method will be used. For the evaluation of the forecasting methods, we applied forecasting accuracy measures, mean absolute percentage error (MAPE). Based on the results of ARIMA and SutteARIMA forecasting methods, it can be concluded that the SutteARIMA method is more suitable than ARIMA to calculate the daily forecasts of confirmed cases of Covid-19 and IBEX in Spain. The MAPE value of 0.036 (smaller than 0.03 compared to MAPE value of ARIMA) for confirmed cases of Covid-19 in Spain and was in the amount of 0.026 for IBEX stock. At the end of the analysis, this study used the SutteARIMA method, this study calculated daily forecasts of confirmed cases of Covid-19 in Spain from 10 April 2020 until 12 April 2020 i.e. 158925; 164390; and 169969 and Spain Stock Market from 14 April 2020 until 16 April 2020 i.e. 7000.61; 6930.61; and 6860.62.