Predicting the Spread of the Corona Virus (COVID-19) in Indonesia: Approach Visual Data Analysis and Prophet Forecasting

Amir Mahmud Husein(1*), Jefri Poltak Hutabarat(2), Jeckson Edition Sitorus(3), Tonazisokhi Giawa(4), Mawaddah Harahap(5),


(1) Universitas Prima Indonesia
(2) Universitas Prima Indonesia
(3) Universitas Prima Indonesia
(4) Universitas Prima Indonesia
(5) Universitas Prima Indonesia
(*) Corresponding Author

Abstract


The development trend of the coronavirus pandemic (COVID-19) in various countries has become a global threat, including in Southeast Asia, such as Indonesia, the Philippines, Brunei, Malaysia, and Singapore. In this paper, we propose an Exploratory Data Analysis (EDA) model approach and a time series forecasting model using the Prophet method to predict the number of confirmed cases and cases of death in Indonesia in the next thirty days. We apply the EDA model to visualize and provide an understanding of this pandemic outbreak in various countries, especially in Indonesia. We present the trends in the spread of epidemics from the countries of China from which the virus originates, then mark the top ten countries and their development and also present the trends in Asian countries. We present an analytical framework comparing the predicted results with the actual data evaluated using the MAPE and MAE models, where the prophet algorithm produces good performance based on the evaluation results, the relative error rate of our estimate (MAPE) is around 6.52%, and the model average false 52.7% (MAE) for confirmed cases, while case mortality was 1.3% for the MAPE and MAE models around 236.6%. The results of the analysis can be used as a reference for the Indonesian government in making decisions to prevent its spread in order to avoid an increase in the number of deaths

Keywords


Exploratory Data Analysis; Prophet; Coronavirus; COVID-19; Forecasting

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References


. Anastassopoulou, C., Russo, L., Tsakris, A., & Siettos, C. (2020). Data-based analysis, modelling and forecasting of the COVID-19 outbreak. PLoS One, 15(3), e0230405. https://doi.org/10.1371/journal.pone.0230405

. Turiel, J., & Aste, T. (2020). Wisdom of the crowds in forecasting COVID-19 spreading severity. 9–10. Retrieved from http://arxiv.org/abs/2004.04125

. Li, L., Yang, Z., Dang, Z., Meng, C., Huang, J., Meng, H., … Peng, H. (2020). Propagation analysis and prediction of the COVID-19. MedRxiv, 12, 2020.03.14.20036202. https://doi.org/10.1101/2020.03.14.20036202

. Liu, D., Clemente, L., Poirier, C., Ding, X., Chinazzi, M., Davis, J. T., … Santillana, M. (2020). A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models. (d). Retrieved from http://arxiv.org/abs/2004.04019

. Singh, R., & Adhikari, R. (2020). Age-structured impact of social distancing on the COVID-19 epidemic in India. (March). Retrieved from http://arxiv.org/abs/2003.12055

. Crokidakis, N. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. Retrieved from http://arxiv.org/abs/2003.12150

. Zhou, X., Hong, N., Ma, Y., He, J., Jiang, H., & Liu, C. (2020). Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model.

. Gupta, R., & Pal, S. K. (2020). Trend Analysis and Forecasting of COVID-19 outbreak in India. MedRxiv, 2020.03.26.20044511. https://doi.org/10.1101/2020.03.26.20044511

. Roosa, K., Lee, Y., Luo, R., Kirpich, A., Rothenberg, R., Hyman, J. M., … Chowell, G. (2020). Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020. Infectious Disease Modelling, 5, 256–263. https://doi.org/10.1016/j.idm.2020.02.002

. Manchein, C., Brugnago, E. L., da Silva, R. M., Mendes, C. F. O., & Beims, M. W. (2020). Strong correlations between power-law growth of COVID-19 in four continents and the inefficiency of soft quarantine strategies. 1–10. Retrieved from http://arxiv.org/abs/2004.00044

. Pal, R., Sekh, A. A., Kar, S., & Prasad, D. K. (2020). Neural network based country wise risk prediction of COVID-19. d, 1–9. Retrieved from http://arxiv.org/abs/2004.00959

. Al-qaness, M. A. A., Ewees, A. A., Fan, H., & Abd El Aziz, M. (2020). Optimization Method for Forecasting Confirmed Cases of COVID-19 in China. Journal of Clinical Medicine, 9(3), 674. https://doi.org/10.3390/jcm9030674

. Elmousalami, H. H., & Hassanien, A. E. (2020). Day Level Forecasting for Coronavirus Disease (COVID-19) Spread: Analysis, Modeling and Recommendations. Retrieved from http://arxiv.org/abs/2003.07778

. Bezerra, A., Silva, I., Guedes, L. A., Silva, D., Leitão, G., & Saito, K. (2019). Extracting value from industrial alarms and events: A data-driven approach based on exploratory data analysis. Sensors (Switzerland), 19(12). https://doi.org/10.3390/s19122772

. Khan, A. M., Siddiqi, M. H., & Lee, S. W. (2013). Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones. Sensors (Switzerland), 13(10), 13099–13122. https://doi.org/10.3390/s131013099

. Ma, D., Fan, H., Li, W., & Ding, X. (2019). The state of mapillary: An exploratory analysis. ISPRS International Journal of Geo-Information, 9(1). https://doi.org/10.3390/ijgi9010010

. Ma, X., Hummer, D., Golden, J. J., Fox, P. A., Hazen, R. M., Morrison, S. M., … Meyer, M. B. (2017). Using visual exploratory data analysis to facilitate collaboration and hypothesis generation in cross-disciplinary research. ISPRS International Journal of Geo-Information, 6(11). https://doi.org/10.3390/ijgi6110368

. Taylor, S. J., & Letham, B. (2017). Forcast at Scale Prophet. PeerJ Preprints, 1–25. https://doi.org/10.7287/peerj.preprints.3190v2




DOI: https://doi.org/10.29099/ijair.v5i1.192

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