Backpropagation with BFGS Optimizer for Covid-19 Prediction Cases in Surabaya

Zuraidah Fitriah, Mohamad Handri Tuloli, Syaiful Anam, Noor Hidayat, Indah Yanti, Dwi Mifta Mahanani

Abstract


Covid-19 is a new type of corona virus called SARS-CoV-2. One of the cities that has contributed the most to infected Covid-19 cases in Indonesia is Surabaya, East Java. Predicting the Covid-19 is the important thing to do. One of the prediction methods is Artificial Neural Network (ANN). The backpropagation algorithm is one of the ANN methods that has been successfully used in various fields. However, the performance of backpropagation is depended on the architecture and optimization method. The standard backpropagation algorithm is optimized by gradient descent method. The Broyden - Fletcher - Goldfarb - Shanno (BFGS) algorithm works faster then gradient descent. This paper was predicting the Covid-19 cases in Surabaya using backpropagation with BFGS. Several scenarios of backpropagation parameters were also tested to produce optimal performance. The proposed method gives better results with a faster convergence then the standard backpropagation algorithm for predicting the Covid-19 cases in Surabaya.


Keywords


Covid-19; Surabaya; prediction; backpropagation; BFGS

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References


A. I. Saba and A. H. Elsheikh, "Forecasting the prevalence of COVID-19 outbreak in Egypt using nonlinear autoregressive artificial neural networks," in Process Safety and Environmental Protection, pp. 1-8, 2020.

A. Rodríguez, G. Moreno, J. Gómez, R. Carbonell, E. Picó-Plana, C. B. Bofill, R. S. Parrilla, S. Trefler, E. E. Pitarch, L. Canadell, X. Teixido, L. Claverias, M. Bodí, and on behalf of the HJ23-COVID-19 working group, “Severe infection due to the SARS-CoV-2 coronavirus: Experience of a tertiary hospital with COVID-19 patients during the 2020 pandemic,” in Medicina Intensiva, pp. 525-533, 2020.

D. Annane, N. Heming, L. Grimaldi-Bensouda, V. Fremeaux-Bacchi, M. Vigan, A.-L. Roux, A. Marchal, H. Michelon, M. Rottman, and P. Moine, “Eculizumab as an emergency treatment for adult patients with severe COVID-19 in the intensive care unit: A proof-of-concept study,” in EclinicalMedicine, 2020.

D. Aldila, H. A. Sarbaz, Khoshnaw, E. Safitri, Y. R. Anwar, R. Q. Aanisah, Bakry, B. M. Samiadji, D. A. Anugerah, M. F. Alfarizi, I. D. Ayulani, and S. N. Salim, "A mathematical study on the spread of COVID-19 considering social distancing and rapid assessment: The case of Jakarta, Indonesia," in Chaos, Solitons and Fractals, 2020.

H. D. Windarwati, W. Oktaviana, I. Mukarromah, N. A. L. Ati, A. F. Rizzal, and A. D. Sulaksono, "In the middle of the COVID-19 outbreak: Early practical guidelines aspects of COVID-19 in East Java, Indonesia", in Psychiatry Research, 2020.

https://lawanCovid-19.surabaya.go.id/visualisasi/graph diakses pada 16 November 2020.

M. K. Kim, Y. S. Kim, and J. Srebric, "Impact of Correlation of Plug Load Data, Occupancy Rates and Local Weather Conditions on Electricity Consumption in a Building Using Four Back-propagation Neural Network Models Sustainable Cities and Society," 2020, doi: https://doi.org/10.1016/j.scs.2020.102321

M. Somasundaram, P. Latha, and S. A. S. Pandian, "Curriculum Design Using Artificial Intelligence (AI) Back Propagation Method," in 9th World Engineering Education Forum, WEEF, 2019.

N. Andrei 2017. "Double parameter scaled BFGS method for unconstrained optimization," in Journal of Computational and Applied Mathematics, 2017, doi: https://doi.org/10.1016/j.cam.2017.10.009

R. Djalante, J. Lassa, D. Setiamarga, A. Sudjatma, M. Indrawan, B. Haryanto, C. Mahfud, M. S. Sinapoy, S. Djalante, I. Rafliana, L. A. Gunawan, G. A. K. Surtiari, H. Warsilah, “Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020,” in Progress in Disaster Sciencs, 2020.

R. Golpe, L. A. Pérez-de-Llano, D. Dacal, H. Guerrero-Sande, B. Pombo-Vide, P. Ventura-Valcárcel, and On behalf of the Lugo Covid-19 team, “Risk of severe COVID-19 in hypertensive patients treated with renin-angiotensin-aldosterone system inhibitors” in Medicina Clinica, pp. 488–490, 2020.

R. Tosepu, J. Gunawan, D. S. Effendy, L. O. A. I. Ahmad, H. Lestari, H. Bahar, and P. Asfian, "Correlation between weather and Covid-19 pandemic in Jakarta, Indonesia," in Science of the Total Environment, 2020.

S. Anam, "Rainfall prediction using backpropagation algorithm optimized by Broyden-Fletcher-Goldfarb-Shanno algorithm," in IOP Conf. Series: Materials Science and Engineering, 2019.

S. Annas, M. I. Pratama, M. Rifandi, W. Sanusi, and S. Side, "Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia," in Chaos, Solitons and Fractals, 2020.

Z. Malki, E. Atlam, A. E. Hassanien, G. Dagnew, M. A. Elhosseini, and I. Gad, "Association between weather data and COVID-19 pandemic predicting mortality rate: Machine learning approaches," in Chaos, Solitons and Fractals, 2020.




DOI: https://doi.org/10.31315/telematika.v18i2.5454

DOI (XML): https://doi.org/10.31315/telematika.v18i2.5454.g3826

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TELEMATIKA: Jurnal Informatika dan Teknologi Informasi
ISSN 1829-667X (print); ISSN 2460-9021 (online)


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