QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019

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....

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Main Authors: Wahidah Sanusi, Sukarna Sukarna, Nur Harisahani
Format: Article
Language:English
Published: Universitas Pattimura 2023-04-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5810
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author Wahidah Sanusi
Sukarna Sukarna
Nur Harisahani
author_facet Wahidah Sanusi
Sukarna Sukarna
Nur Harisahani
author_sort Wahidah Sanusi
collection DOAJ
description 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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language English
publishDate 2023-04-01
publisher Universitas Pattimura
record_format Article
series Barekeng
spelling doaj-art-7da27c7d3f014423bba273ce15900ca82025-08-20T03:35:55ZengUniversitas PattimuraBarekeng1978-72272615-30172023-04-011710001000810.30598/barekengvol17iss1pp0001-00085810QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019Wahidah Sanusi0Sukarna Sukarna1Nur Harisahani2Department of Mathematics, FMIPA, Universitas Negeri Makassar, IndonesiaDepartment of Mathematics, FMIPA, Universitas Negeri Makassar, IndonesiaDepartment of Mathematics, FMIPA, Universitas Negeri Makassar, IndonesiaMakassar 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.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5810quantile regressionrainfallmakassarseasonal data
spellingShingle Wahidah Sanusi
Sukarna Sukarna
Nur Harisahani
QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
Barekeng
quantile regression
rainfall
makassar
seasonal data
title QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
title_full QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
title_fullStr QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
title_full_unstemmed QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
title_short QUANTILE REGRESSION MODEL ON RAINFALL IN MAKASSAR 2019
title_sort quantile regression model on rainfall in makassar 2019
topic quantile regression
rainfall
makassar
seasonal data
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5810
work_keys_str_mv AT wahidahsanusi quantileregressionmodelonrainfallinmakassar2019
AT sukarnasukarna quantileregressionmodelonrainfallinmakassar2019
AT nurharisahani quantileregressionmodelonrainfallinmakassar2019