Mask Compliance Modeling Related COVID-19 in Indonesia Using Spline Nonparametric Regression

  • Citra Imama Universitas Airlangga
  • M. Haykal Adriansyah Universitas Airlangga
  • Hadi Prayogi Universitas Airlangga
  • Ferdiana Friska Rahmana Putri Universitas Airlangga
  • Naufal Ramadhan Al Akhwal Siregar Universitas Airlangga
  • Alfredi Yoani Universitas Airlangga
  • Fariz Mardianto Universitas Airlangga
Keywords: COVID-19, SDGs, Mask Compliance, Nonparametric Regression, Spline Estimator


Until now, Coronavirus disease (COVID-19) has become a concern for Indonesia because of its significant development and impact on various sectors of life and hampering the target of achieving Sustainable Development Goals (SDGs). The achievements targeted in the SDGs, such as reducing poverty, hunger, and many more are very difficult to realize in the current pandemic conditions. The uncertain conditions of the pandemic made the government need some new ideas for consideration in creating policies to encourage sustainable development in this situation. This article covers modeling the effect of achieving the second dose of vaccination and the total cases of COVID-19 cases, which are often considered the reason for general negligence in complying with health protocols, especially wearing masks. This research was conducted using spline nonparametric regression because of its flexibility to handle uncertain data patterns. The results of this study are truncated spline nonparametric regression with 3 knots that produce a R-sq equal to 69.952%. Based on the results, the second dose vaccination coverage variables and the total COVID-19 cases together affect mask compliance. This result is expected to be a benchmark for the government to handle COVID-19 and efforts to achieve the SDGs.


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How to Cite
C. Imama, “Mask Compliance Modeling Related COVID-19 in Indonesia Using Spline Nonparametric Regression”, Jurnal Varian, vol. 5, no. 2, pp. 179 - 190, May 2022.