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All Journal JC-T (Journal Cis-Trans) : Jurnal Kimia dan Terapannya
Agung Hari Saputra
Program Studi Meteorologi, Sekolah Tinggi Meteorologi Klimatologi dan Geofisika, Indonesia
Biochemistry, Genetics & Molecular Biology

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Pemanfaatan Pemodelan Machine Learning dalam Memprediksi Parameter Kualitas Udara Nitrogen Dioksida (NO2) Berdasarkan Algoritma Extra Trees Regression di DKI Jakarta Muhammad Aulia Zikri; I Wayan Jyesta Jaya Taruna; Juang Merdeka; Agung Hari Saputra
JC-T (Journal Cis-Trans) : Jurnal Kimia dan Terapannya Vol. 7 No. 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um0260v7i22023p031

Abstract

The study examined the air quality in DKI Jakarta, mainly on the nitrogen dioxide (NO2) parameters, using the Extra Trees Regression model to predict the NO2 index. The study used the 2022 NO2 time series data, which showed no significant long-term trends and indicated stationary and random data. Periodogram, histogram, and Q-Q plot analysis showed normal distribution with minor deviations. No significant autocorrelation was found between actual NO2 data and model data, indicating the possibility of white noise. Evaluation of models with parameters such as MASE, MAE, RMSE, MAPE, SMAPE, and R2 showed good model performance. An R2 value of 73.14% indicates a model's ability to explain actual data variability. Although the Extra Trees Regression model follows seasonal patterns, there is an inconsistency between actual values and predictions at some points. This indicates a potential overfitting or difficulty in capturing specific data patterns. This research provides modeling information that is suitable for predicting air quality in DKI Jakarta.
Co-Authors I Wayan Jyesta Jaya Taruna Juang Merdeka Muhammad Aulia Zikri