skip to main content


*Tiani Wahyu Utami  -  Program Study of Statistics, Universitas Muhammadiyah Semarang, Indonesia
Aisyah Lahdji  -  Medical Faculty, University Muhammadiyah Semarang, Indonesia
Open Access Copyright (c) 2021 MEDIA STATISTIKA under

Citation Format:
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which was recently discovered. Coronavirus disease is now a pandemic that occurs in many countries in the world, one of which is Indonesia. One of the cities in Indonesia that has found many COVID cases is Semarang city, located in Central Java. Data on cases of COVID patients in Semarang City which are measured daily do not form a certain distribution pattern. We can build a model with a flexible statistical approach without any assumptions that must be used, namely the nonparametric regression. The nonparametric regression in this research using Local Polynomial Kernel approach. Determination of the polynomial order and optimal bandwidth in Local Polynomial Kernel Regression modeling use the GCV (Generalized Cross Validation) method. The data used this research are data on the number of COVID patients daily cases in Semarang, Indonesia. Based on the results of the application of the COVID patient daily cases in Semarang City, the optimal bandwidth value is 0.86 and the polynomial order is 4 with the minimum GCV is 3179.568 so that the model estimation results the MSE is 2922.22 and the determination coefficient is 97%. The estimation results show the highest number of Corona in the Semarang City at the beginning of July 2020. After the corona case increased in July, while the corona case in August decreased.

Note: This article has supplementary file(s).

Fulltext View|Download |  Research Instrument
Type Research Instrument
  Download (140KB)    Indexing metadata
Keywords: COVID; generalized cross validation; local polynomial kernel; nonparametric regression
Funding: LPPM Universitas Muhammadiyah Semarang

Article Metrics:

  1. Adelia, L. (2020). Update Virus Corona Kota Semarang Jumat 7 Agustus 2020, Tertinggi Tembalang Terendah Tugu. Tribun Jateng.
  2. Aida, N. . (2020). Update Virus Corona di Dunia: 214.894 Orang Terinfeksi, 83.313 Sembuh, 8.732 Meninggal Dunia. Kompas.Com.
  3. Budiantara, I. ., & Mulianah. (2007). Pemilihan Banwidth Optimal dalam Regresi Semiparametrik Kernel dan Aplikasinya. Journal Sains Dan Teknoogi SIGMA, 10, 159–166
  4. Djalante, R., Lassa, J., Setiamarga, D., Sudjatma, A., Indrawan, M., Haryanto, B., Mahfud, C., Sinapoy, M. S., Djalante, S., Rafliana, I., Gunawan, L. A., Surtiari, G. A. K., & Warsilah, H. (2020). Review and Analysis of Current Responses to COVID-19 in Indonesia: Period of January to March 2020. Progress in Disaster Science, 6.
  5. Fan, J., & Gijbels, I. (1998). Local Polynomial Modelling and its Aplications. Chapman and Hall
  6. Fitra, S. (2020). Perkembangan Terkini COVID-19 di Indonesia : Total Kasus Capai 56.385. Katadata.
  7. Hadijati, M. (2004). Estimasi Kernel dalam Regresi Nonparametrik dengan Error Berkorelasi. Institut Teknologi Sepuluh Nopember, Surabaya
  8. Hardle, W. (1990). Applied Nonparametric Regression. Cambridge University Press
  9. Hong, S. Y. (1999). Automatic bandwidth choice in a semiparametric regression model. Statistica Sinica, 9(3), 775–794
  10. Sebayang, R. (2020). Awas! WHO Akhirnya Tetapkan Corona Darurat Global. CNBC Indonesia
  11. Utami, T. . (2013). Estimasi Kurva Regresi Semiparametrik Pada Data Longitudinal Berdasarkan Estimator. Statistika, 1(1), 30–36
  12. Utami, T. ., & Nur, I. . (2014). Longitudinal Data Modeling Based on Platelets Level in DHF (Dengue Hemorrhagic Fever) Using Nonparametric Regression of Local Polynomial Kernel GEE Approach. International Conference on Biomedical Engineering Technology and Application (ICBETA)
  13. Utami, T. W., Haris, M. A., Prahutama, A., & Purnomo, E. A. (2020). Optimal Knot Selection in Spline Regression using Unbiased Risk and Generalized Cross Validation Methods. Journal of Physics: Conference Series, 1446(1).
  14. Utami, T. W., Prahutama, A., Karim, A., & Achmad, A. R. F. (2019). Modelling Rice Production in Central Java using Semiparametric Regression of Local Polynomial Kernel Approach. Journal of Physics: Conference Series, 1217(1).
  15. WHO. (2020). Coronavirus Disease 2019 (COVID-19): Situation Report
  16. Wikipedia. (2019). Coronavirus Disease 2019. Wikipedia.
  17. Wu, H., & Zhang, J. (2006). Nonparametric Regression Methods for Longitudinal Data Analysis : Mixed- Effects Modeling Approaches Nonparametric Mixed-Effects Models for Longitudinal Data Analysis (Issue March).

Last update:

No citation recorded.

Last update: 2024-02-23 12:50:15

No citation recorded.