Analisis Kumulatif dan Survival Model Sebaran Covid-19 Provinsi Papua Tahun 2021
DOI:
https://doi.org/10.31851/sainmatika.v19i1.7890Keywords:
COVID-19 data, Papua, distribution, cumulative and survival analysis.Abstract
After the government implemented the Implementation of Community Activity Restrictions (PPKM) in August 2021, COVID-19 cases in Papua Province had decreased by 46.2%. The daily average of COVID-19 cases in July decreased from 370 to 119 cases to be precise in August 2021. One of the Jayapura City government policies in early 2022 that aimed to break the chain of COVID-19 spread was to eliminate face-to-face learning for Kindergarten, Elementary, Junior High, and High School education levels from February 15 - March 15, 2022. Previous research related to the analysis of the cumulative distribution of COVID-19 in Papua province had been carried out in 2021. It used data on COVID-19 cases for two months during September 1 - October 31, 2020. The researchers used the Johnson SB model. In contrast to previous studies, the present study aimed to use the distribution of Erlang, Fatigue Life, Frechet, Gamma, Logistics, Pareto, Pearson Type 5 and Weibull to perform a cumulative and survival analysis on positive cases of COVID-19 patients in Papua Province in 2021. In addition, This study used COVID-19 data from January to April 2021. The results showed that the analysis of COVID-19 data in Papua Province in 2021 can utilize the Fatigue Life, Frechet, Gamma, Logistics, Pearson Type 5 and Weibull models.
References
Abd El-Monsef, M. M. E. (2021). Erlang mixture distribution with application on COVID-19 cases in Egypt. International Journal of Biomathematics. https://doi.org/10.1142/S1793524521500157
Abd El-Monsef, M. M. E., & Al-Kzzaz, H. S. (2021). Inverse power frÈchet distribution: Statistical properties, estimation and application. Global and Stochastic Analysis.
Ai, Y., Zhu, S. P., Liao, D., Correia, J. A. F. O., Souto, C., De Jesus, A. M. P., & Keshtegar, B. (2019). Probabilistic modeling of fatigue life distribution and size effect of components with random defects. International Journal of Fatigue. https://doi.org/10.1016/j.ijfatigue.2019.05.005
Alfaer, N. M., Gemeay, A. M., Aljohani, H. M., & Afify, A. Z. (2021). The extended log-logistic distribution: Inference and actuarial applications. Mathematics. https://doi.org/10.3390/math9121386
Arino, J., & Portet, S. (2020). A simple model for COVID-19. Infectious Disease Modelling. https://doi.org/10.1016/j.idm.2020.04.002
Bai, L., & Kalaj, D. (2021). Approximation of Kolmogorov–Smirnov test statistic. Stochastics. https://doi.org/10.1080/17442508.2020.1844705
Baumgartner, D., & Kolassa, J. (2021). Power considerations for Kolmogorov–Smirnov and Anderson–Darling two-sample tests. Communications in Statistics: Simulation and Computation. https://doi.org/10.1080/03610918.2021.1928193
Dagpunar, J. (2019). The gamma distribution. Significance. https://doi.org/10.1111/j.1740-9713.2019.01226.x
Gunawan, G. G., Besperi, B., & Purnama, L. (2020). Analisis Debit Banjir Rancangan Sub DAS Air Bengkulu Menggunakan Analisis Frekuensi dan Metode Distribusi. Jurnal Ilmiah Rekayasa Sipil. https://doi.org/10.30630/jirs.17.1.298
Hanusz, Z., & Tarasińska, J. (2015). Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality. Biometrical Letters. https://doi.org/10.1515/bile-2015-0008
Hincal, E., & Alsaadi, S. (2019). Posterior analysis of weighted Erlang distribution. AIP Conference Proceedings. https://doi.org/10.1063/1.5136185
Ibrahim, A., & Kalaf, B. A. (2022). Estimation of the survival function based on the log-logistic distribution. International Journal of Nonlinear Analysis and Applications. https://doi.org/10.22075/IJNAA.2022.5466
Kamalov, F., & Denisov, D. (2020). Gamma distribution-based sampling for imbalanced data. Knowledge-Based Systems. https://doi.org/10.1016/j.knosys.2020.106368
Lei, W. S., Zhang, P., Yu, Z., & Qian, G. (2020). Statistics of ceramic strength: Use ordinary Weibull distribution function or Weibull statistical fracture theory? Ceramics International. https://doi.org/10.1016/j.ceramint.2020.05.024
Lima, S. R., & Cordeiro, G. M. (2017). The extended log-logistic distribution: Properties and application. Anais Da Academia Brasileira de Ciencias. https://doi.org/10.1590/0001-3765201720150579
Liu, F., Zhou, S., Xia, C., Zeng, D., & Shi, T. (2016). Optimization of fatigue life distribution model and establishment of probabilistic S–N curves for a 165 ksi grade super high strength drill pipe steel. Journal of Petroleum Science and Engineering. https://doi.org/10.1016/j.petrol.2016.06.018
Malik, A. S., & Ahmad, S. P. (2020). An Extension of Log-Logistic Distribution for Analyzing Survival Data. Pakistan Journal of Statistics and Operation Research. https://doi.org/10.18187/PJSOR.V16I4.2961
Mierlus-Mazilu, I. (2010). On generalized pareto distributions. Romanian Journal of Economic Forecasting.
Nadarajah, S., & Gupta, A. K. (2006). Some bivariate gamma distributions. Applied Mathematics Letters. https://doi.org/10.1016/j.aml.2005.10.007
Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk , Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics. https://doi.org/doi:10.1515/bile-2015-0008
Reba, F., & Sroyer, A. (2021). Analisis Kumulatif Covid-19 Provinsi Papua Tahun 2020 Menggunakan Model Distribusi Johnson Sb. STATISTIKA Journal of Theoretical Statistics and Its Applications, 21(1), 21–28. https://doi.org/10.29313/jstat.v21i1.7820
Shahbaz, S. H., Al-Sobhi, M., Shahbaz, M. Q., & Al-Zahrani, B. (2018). A new multivariate Weibull distribution. Pakistan Journal of Statistics and Operation Research. https://doi.org/10.18187/pjsor.v14i1.2192
Sharpe, J., & Juárez, M. A. (2021). Estimation of the Pareto and related distributions–A reference-intrinsic approach. Communications in Statistics - Theory and Methods. https://doi.org/10.1080/03610926.2021.1916826
Sijbers, J., Den Dekker, A. J., Scheunders, P., & Van Dyck, D. (1998). Maximum-likelihood estimation of rician distribution parameters. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/42.712125
Sukkiramathi, K., & Seshaiah, C. V. (2020). Analysis of wind power potential by the three-parameter Weibull distribution to install a wind turbine. Energy Exploration and Exploitation. https://doi.org/10.1177/0144598719871628
Sutrisno, A. J., Kaswanto, & Hadi Susilo. (2020). Analisis Prediksi dan Hubungan antara Debit Air dan Curah Hujan pada Sungai Ciliwung di Kota Bogor. Jurnal Pengelolaan Sumberdaya Alam Dan Lingkungan (Journal of Natural Resources and Environmental Management). https://doi.org/10.29244/jpsl.10.1.25-33
Tejo, M., Niklitschek-Soto, S., & Marmolejo-Ramos, F. (2018). Fatigue-life distributions for reaction time data. Cognitive Neurodynamics. https://doi.org/10.1007/s11571-017-9473-x
Wais, P. (2017). Two and three-parameter Weibull distribution in available wind power analysis. Renewable Energy. https://doi.org/10.1016/j.renene.2016.10.041
Wang, S., & Gui, W. (2020). Corrected maximum likelihood estimations of the lognormal distribution parameters. Symmetry. https://doi.org/10.3390/SYM12060968
Wickramaarachchi, T. N. (2021). Flood Discharge Estimation in Baddegama Using Pearson Type III and Gumbel Distributions. In Springer Water. https://doi.org/10.1007/978-3-319-54612-4_24
Wu, M. H., Wang, J. P., & Ku, K. W. (2019). Earthquake, Poisson and Weibull distributions. Physica A: Statistical Mechanics and Its Applications. https://doi.org/10.1016/j.physa.2019.04.237
Yang, F., Ren, H., & Hu, Z. (2019). Maximum likelihood estimation for three-parameter weibull distribution using evolutionary strategy. Mathematical Problems in Engineering. https://doi.org/10.1155/2019/6281781
Zayed, M., & Butt, N. S. (2017). The extended Fréchet distribution: Properties and applications. Pakistan Journal of Statistics and Operation Research. https://doi.org/10.18187/pjsor.v13i3.2058
Zheng, X., Chiang, J. Y., Tsai, T. R., & Wang, S. (2021). Estimating the failure rate of the log-logistic distribution by smooth adaptive and bias-correction methods. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2021.107188
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