INTERPOLASI POLUTAN NITROGEN DIOKSIDA (NO2) DENGAN PENDEKATAN ORDINARY KRIGING DAN INVERSE DISTANCE WEIGHTED (STUDI KASUS DI KOTA YOGYAKARTA)
DOI:
https://doi.org/10.34123/jurnalasks.v14i2.359Keywords:
Nitrogen Dioksida, Ordinary Kriging, Inverse Distance Weighted, Root Mean Square ErrorAbstract
Permasalahan yang kerap terjadi di kota-kota besar adalah pencemaran udara. Nitrogen Dioksida (NO2) merupakan salah satu zat pencemar udara berbahaya yang berkontribusi besar terhadap pencemaran udara. Dalam rangka pemantauan kualitas udara ambien, maka Dinas Lingkungan Hidup Kota Yogyakarta melakukan pengukuran di beberapa titik lokasi untuk mengetahui konsentrasi dari zat pencemar tersebut. Namun karena pengukuran memerlukan proses yang panjang dan terhalang dana yang besar, maka pengukuran tidak dilakukan di semua titik lokasi. Oleh karena itu, diperlukan suatu metode interpolasi spasial untuk mengestimasi konsentrasi NO2 di Kota Yogyakarta yang lokasinya tidak dilakukan pengukuran. Metode yang digunakan adalah Ordinary Kriging (OK) dan Inverse Distance Weighted (IDW). Dari hasil analisis diperoleh bahwa metode yang paling akurat untuk estimasi konsentrasi NO2 di Kota Yogyakarta adalah OK. Hal ini dikarenakan hasil perhitungan nilai Root Mean Square Error (RMSE) pada OK lebih kecil, yaitu 0.4847 dibanding 0.5224 pada IDW
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Alfiana, A. N. (2010). Metode ordinary kriging pada geostatistika.
American Lung. (2020). Nitrogen Dioxide. https://www.lung.org/clean-air/outdoors/what-makes-air-unhealthy/nitrogen-dioxide
Chang, K. (2018). An Introduction to Geographic Information Systems. In Libraries (9th ed.). McGraw-Hill Education. https://doi.org/10.1201/b12440-10
Cressie, N. A. (1993). Statistics for spatial data. Wiley-interscience Publication.
Defra. (2009). Departmental Report 2009. In Secretary. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/228738/7599.pdf
Dinas Lingkungan Hidup Kota Yogyakarta. (2019). Laporan analisa hasil pemantauan kualitas udara (Issue 1). https://lingkunganhidup.jogjakota.go.id/page/index/kualitas-air-dan-udara
Dorman, M. (2021). Spatial interpolation of point data. In Introduction to Spatial Data Programming with R. Ben-Gurion University of the Negev. http://132.72.155.230:3838/r/spatial-interpolation-of-point-data.html
Environment Agency of DKI Jakarta, & Strategis, V. (2020). Toward clean air Jakarta. 1–56. http://jakarta.cleanair.id
Fridayani, N. M. S., Kencana, I. P. E. N., & Sukarsa, K. G. (2012). Perbandingan interpolasi spasial dengan metode ordinary dan robust kriging pada data spasial berpencilan (studi kasus: curah hujan di kabupaten Karangasem). E-Jurnal Matematika, 1(1), 68–74. https://doi.org/10.24843/mtk.2012.v01.i01.p012
Green Facts. (2005). Air pollution Nitrogen Dioxide. https://www.greenfacts.org/en/nitrogen-dioxide-no2/index.htm#1
Hao, T., Zhong, L., Zhu, T., Zhang, X., Wang, X., & Zhang, L. (2020). A new prediction method of reservoir porosity based on improved Kriging interpolation. Journal of Physics: Conference Series, 1707(1). https://doi.org/10.1088/1742-6596/1707/1/012018
Hatfield, G. (2018). Spatial statistics. Practical Mathematics for Precision Farming, 75–104. https://doi.org/10.2134/practicalmath2016.0102
Johnston, K., Hoef, J. M. Ver, Krivoruchko, K., & Lucas, N. (2003). ArcGIS 9: Using ArcGIS geostatistical analyst. ESRI. https://doi.org/10.1111/1467-9671.00074
Joly, D., Thierry, B., Cardot, H., Cavailhès, J., Hilal, M., & Wavresky, P. (2009). Interpolation Par Régressions Locales. L'Espace Géographique, 157-170.
Lloyd, C. D., & Atkinson, P. M. (2004). Increased Accuracy of Geostatistical Prediction of Nitrogen Dioxide in the United Kingdom with Secondary Data. International Journal of Applied Earth Observation and Geoinformation, 293-305.
Mohebzadeh, H. (2018). Comparison of methods for fitting the theoretical variogram to the experimental variogram for estimation of depth to groundwater and its temporal and spatial Variations. American-Eurasian Journal of Agricultural and Environmental Science, 18(2), 64–76. https://doi.org/10.5829/idosi.aejaes.2018.64.76
Nasional, B. P. P. (2006). Peluncuran dokumen strategi dan rencana aksi nasional dan 5 kota besar untuk peningkatan kualitas udara perkotaan. 2. https://www.bappenas.go.id/files/2913/5039/6566/pressreleasedocedited__20081123205824__1291__0.pdf
Peter M, A., & Christopher D, L. (2009). Geostatistics and spatial interpolation. In The SAGE handbook of spatial analysis. https://www.doi.org/10.4135/9780857020130
Prabowo, K., & Muslim, B. (2018). Penyehatan Udara. http://bppsdmk.kemkes.go.id/pusdiksdmk/wp-content/uploads/2018/09/Penyehatan-Udara_SC.pdf
Rofienda. (2004). Dampak Negatif Pencemaran Nitrogen Dioksida, Usaha Pencegahan dan Penanggulangannya (pp. 27–32). http://ejournal.kemenperin.go.id/jkk/article/view/4706/3613
Sreedhar, B. R., & Muthyalappa, K. (2020). Rainfall forecast through root mean squared error using double exponential & log-pearson iii probability distributions . 7(8), 5266–5272.
Zhang, X., Lian, L., & Zhu, F. (2021). Parameter fitting of variogram based on hybrid algorithm of particle swarm and artificial fish swarm. Future Generation Computer Systems, 116, 265–274. https://doi.org/10.1016/j.future.2020.09.026
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Published
2022-12-30
How to Cite
Safira, M. C., Fauzan, A., & Adhiwibawa, M. A. S. (2022). INTERPOLASI POLUTAN NITROGEN DIOKSIDA (NO2) DENGAN PENDEKATAN ORDINARY KRIGING DAN INVERSE DISTANCE WEIGHTED (STUDI KASUS DI KOTA YOGYAKARTA). Jurnal Aplikasi Statistika & Komputasi Statistik, 14(2), 55–66. https://doi.org/10.34123/jurnalasks.v14i2.359
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