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Andayani, Puji

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Author-ID : 1251699

Biochemistry, Genetics & Molecular Biology Computer Science & IT Education Immunology & microbiology Mathematics Medicine & Pharmacology Neuroscience Other

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Implementation of Holt-Winter Exponential Smoothing Method to Forecast The Spread of Covid-19 Pangestu, Adhitama Ihza; Andayani, Puji
Indonesian Journal of Mathematics and Applications Vol. 1 No. 2 (2023): Indonesian Journal of Mathematics and Applications (IJMA)
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijma.2023.001.02.2

This research examines the Holt winters exponential smoothing method to solve forecasting problems using case studies of the spread of Covid-19. The data source uses the transmission of Covid-19 in Indonesia. MAPE is used to measure errors in data forecasting. The results are structured to serve as a recommendation for other researchers in choosing a method for predicting the spread of the disease. Based on the results, forecasting with the Holt-Winters model in positive cases produces a MAPE value of 9.21% using the Multiplicative model and the best parameter values of alpha, beta and gamma (0.4, 0.05, 0.25). Whereas in the case of human recovery, the MAPE value was 11.86% using the Multiplicative model and the best values for the parameters alpha, beta and gamma (0.4, 0.03, 0.1). And in the case of death it produces a MAPE of 17.97% using the Multiplicative model and the parameter values alpha, beta and gamma (0.4, 0.01, 0.1). So, it can be concluded that the Holt-Winters method on human positive case data shows a good outcome performance while recovered and deceased cases produce a well-being analysis performance.

Implementation of Holt-Winter Exponential Smoothing Method to Forecast The Spread of Covid-19 Pangestu, Adhitama Ihza; Andayani, Puji
Indonesian Journal of Mathematics and Applications Vol. 1 No. 2 (2023): Indonesian Journal of Mathematics and Applications
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijma.2023.001.02.2

This research examines the Holt winters exponential smoothing method to solve forecasting problems using case studies of the spread of Covid-19. The data source uses the transmission of Covid-19 in Indonesia. MAPE is used to measure errors in data forecasting. The results are structured to serve as a recommendation for other researchers in choosing a method for predicting the spread of the disease. Based on the results, forecasting with the Holt-Winters model in positive cases produces a MAPE value of 9.21% using the Multiplicative model and the best parameter values of alpha, beta and gamma (0.4, 0.05, 0.25). Whereas in the case of human recovery, the MAPE value was 11.86% using the Multiplicative model and the best values for the parameters alpha, beta and gamma (0.4, 0.03, 0.1). And in the case of death it produces a MAPE of 17.97% using the Multiplicative model and the parameter values alpha, beta and gamma (0.4, 0.01, 0.1). So, it can be concluded that the Holt-Winters method on human positive case data shows a good outcome performance while recovered and deceased cases produce a well-being analysis performance.

Comparing Vector-host and SEIR models for Zika Virus Transmission Andayani, Puji; Azmi, Rizal Dian; Sari, Lisa Risfana
The Journal of Experimental Life Science Vol. 8 No. 3 (2018)
Publisher : Graduate School, Universitas Brawijaya

Some mathematical models to describe Zika virus transmissions have been analyzed. In this study, we construct two models of Zika virus transmission. The first one is the vector-host model. It considers the human population as host and mosquito's population as the vector. The second model is where there is only infected human population who act as transmitter without the existence of infected mosquitoes in the population. The impact of modeling assumption of Zika virus is studied by analyzed the reproduction number using Next Generation Matrix (NGM) method. Formerly, we compare the dynamics of the two models by interpreting the reproduction number of each model. Biologically, the two models cause a similar effect. If the reproduction number is less than one, then the disease is extinct. Otherwise, an endemic condition exists. The numerical simulation also used to explain the comparison of two models. The recovery and the transmission period are solved to compare these two cases. Keywords: comparison, mathematical model, reproduction number, SEIR, Zika Virus.

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