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All Journal JOURNAL OF CIVIL ENGINEERING, BUILDING AND TRANSPORTATION
Sugiarto, Cahya
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Civil Engineering, Building, Construction & Architecture

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The Utilization of HuberRegressor Machine Learning Model to Predict Carbon Monoxide Concentration in Surabaya City Sugiarto, Cahya; Abigael, Febby Debora; Athallah, Yusron Faiz; Agung Hari Saputra
JOURNAL OF CIVIL ENGINEERING BUILDING AND TRANSPORTATION Vol. 8 No. 1 (2024): JCEBT MARET
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jcebt.v8i1.11262

Abstract

Carbon monoxide (CO) is one of the pollutant gases whose concentration currently continues to increase due to an increase in population and population activities, especially those that occur in the city of Surabaya, East Java. The purpose of this study is to make a prediction of CO gas concentration in Surabaya City in 2022. CO concentration air quality data was obtained from MERRA-2 Reanalysis through NASA's Giovanni platform. CO concentration data processing is carried out by Machine Learning methods using the Google Colaboratory platform with the HuberRegressor model. The results of the data processing carried out were obtained with details of MASE worth 0.6218, RMSSE worth 0.3657, MAE worth 0.0280, RMSE worth 0.0314, MAPE worth 0.0836, and SMAPE worth 0.0876. From the results of the evaluation of the model, it can be concluded that the HuberRegressor model can make a prediction of CO gas concentration in the city of Surabaya quite well.
Co-Authors Abigael, Febby Debora Agung Hari Saputra Athallah, Yusron Faiz