IMPLEMENTASI METODE GEOGRAPHICALLY-TEMPORALLY WEIGHTED REGRESSION UNTUK ANALISIS SPASIAL PADA PENCEMARAN UDARA KONSENTRASI PM2.5 DI PROVINSI DKI JAKARTA
DOI:
https://doi.org/10.69714/73tkfs98Keywords:
PM2.5, GTWR, OLS, air pollution, spatial–temporal analysis, DKI JakartaAbstract
This study analyzes the spatial-temporal dynamics of PM2.5 air pollution in DKI Jakarta using the Geographically-Temporally Weighted Regression (GTWR) approach. The objectives of this study are to evaluate the influence of meteorological factors, compare the performance of the global OLS model with GTWR, and identify spatial-temporal heterogeneity in Central Jakarta and North Jakarta using daily data from 2024. The results show that PM2.5 concentrations in both areas exceed WHO and SNI quality standards. The OLS model has limited explanatory power (R² = 0.303), while GTWR significantly improves accuracy (R² = 0.661–0.723) with a decrease in RMSE and MAE. Local estimates show that wind speed and humidity have a negative effect, while air temperature and sunshine duration have a positive effect, with temperature as the dominant factor. Differences in optimal bandwidth between regions confirm the existence of spatial-temporal heterogeneity. This study confirms the superiority of GTWR as an analytical framework to support location- and time-based air pollution control policies.
References
J. Miles, “WHO global air quality guidelines,” Part. matter (PM2.5 PM10), ozone, nitrogen dioxide, sulfur dioxide carbon monoxide., pp. 1–360, 2021.
I. Ismiyati, D. Marlita, and D. Saidah, “Pencemaran udara akibat emisi gas buang kendaraan bermotor,” J. Manaj. Transp. Logistik, vol. 1, no. 3, pp. 241–248, 2014.
AQI Air, “Kualitas Udara di Indonesia.”
K. Polri, “Electronic Registration Identification.”
A. Pratama and A. Sofyan, “Analisis Dispersi Pencemar Udara PM10 di kota Bandung Menggunakan Wrfchem Data Asimilasi,” J. Tek. Lingkung., vol. 26, no. 2, pp. 11–30, 2020.
Ellitan, “UU No 32 tahun 2009,” Экономика Региона, vol. 19, no. 19, p. 19, 2009.
A. S. Fotheringham, B. Lu, M. Charlton, and H. Paul, “Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (review),” Geogr. Anal., vol. 35, no. 3, pp. 272–275, 2003, doi: 10.1353/geo.2003.0008.
K. Aisyiah, Sutikno, and I. N. Latra, “Pemodelan Konsentrasi Partikel Debu (PM10) pada Pencemaran di Kota Surabaya dengan Metode Geographically-Temporally Weighted Regression,” J. Sains dan Seni POMITS, vol. 2, no. 1, pp. 152–157, 2014.
I. F. N. Ilahi, E. Ferdiansyah, and F. Arifianto, “Pendugaan PM2.5 Menggunakan Metode Geographically Temporally Weighted Regression di DKI Jakarta,” J. Ilmu Lingkung., vol. 22, no. 6, pp. 1435–1440, 2024, doi: 10.14710/jil.22.6.1435-1440.
L. Liu et al., “Remote sensing estimation of regional PM2. 5 based on GTWR model-A case study of southwest China,” Environ. Pollut., vol. 351, p. 124057, 2024.
R. A. Regia, V. S. Bachtiar, and R. Solihin, “Analisis Risiko Kesehatan Akibat Paparan Particulate Matter 2,5 (PM2,5) Dalam Rumah Tinggal di Perumahan X Kawasan Industri Semen,” J. Ilmu Lingkung., vol. 19, no. 3, pp. 531–540, 2021, doi: 10.14710/jil.19.3.531-540.
S. Arba, “Dust Respirable Concentration ‘Particulate Matter’ (Pm2.5) And Health Disorders Communities In Settlement Around Electric Steam Power Plant,” Promot. Kesehat. Masy., vol. 9, no. Vol. 9 No. 2: DESEMBER 2019, pp. 178–184, 2019.
C. A. Pope Iii et al., “Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution,” Jama, vol. 287, no. 9, pp. 1132–1141, 2002.
D. Ruhiat and A. Effendi, “Pengaruh Faktor Musiman Pada Pemodelan Deret Waktu Untuk Peramalan Debit Sungai Dengan Metode Sarima,” Teorema, vol. 2, no. 2, p. 117, 2018, doi: 10.25157/.v2i2.1075.
J. H. Seinfeld and S. N. Pandis, Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons, 2016.
S. N. H. F. S. Andri, “Eksplorasi Fluktuasi Konsentrasi PM2.5 di Provinsi Daerah Khusus Jakarta Selama Oktober 2022,” pp. 601–607, 2024.
I. Rizqi, I. P. Santikayasa, and A. Turyanti, “Analisis Pengaruh Faktor Meteorologi terhadap Fluktuasi Analysis of the Influence of Meteorological Factors on Concentration Fluctuation of ?? ? . ? in Pontianak City,” vol. 15, no. 1, pp. 24–33, 2025, doi: 10.26418/positron.v15i1.91566.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Jurnal Ilmiah Multidisiplin Ilmu
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
