QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019

  • Wahidah Sanusi Department of Mathematics, FMIPA, Universitas Negeri Makassar, Indonesia
  • Sukarna Sukarna Department of Mathematics, FMIPA, Universitas Negeri Makassar, Indonesia https://orcid.org/0000-0001-9713-773X
  • Nur Harisahani Department of Mathematics, FMIPA, Universitas Negeri Makassar, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss1pp0001-0008
Keywords: quantile regression, rainfall, Makassar, seasonal data

Abstract

Makassar is an area that has a monsoon rainfall pattern. This study aims to find a quantile regression model and to determine the factors that significantly influence rainfall in the city of Makassar. This applied research applies a quantile regression model to rainfall data which is seasonal data. The advantage of this quantile regression model is that it is able to detect extreme conditions of rainfall, such as heavy rain. The data used is daily data in 2019. The estimation results obtained 9 (nine) models from each quantile used. The best model is obtained based on the largest coefficient of determination ( ), namely the 0,8th quantile ( ) of 0.28%. Furthermore, based on the model, it is found that the factor that significantly influences rainfall in the city of Makassar is humidity. At the same time, the air temperature and wind speed have no significant effect on rainfall in the city of Makassar.

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Published
2023-04-15
How to Cite
[1]
W. Sanusi, S. Sukarna, and N. Harisahani, “QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019”, BAREKENG: J. Math. & App., vol. 17, no. 1, pp. 0001-0008, Apr. 2023.
Issue
Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Wahidah Sanusi, sukarna sukarna, Nur Harisahani

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