Main Article Content

Abstract

Air pollution is a serious matter that must be addressed promptly and quickly. One of the most dangerous pollutants in the air is PM2.5. This pollutant is particulates dust measuring 2.5 micrometers. PM2.5 can cause environmental and health problems such as acute respiratory infections, lung cancer, cardiovascular cancer, and premature death. Air pollution occurs in big cities such as the capital city of Indonesia, DKI Jakarta, which is the city with the highest PM2.5 levels in Indonesia. There are 6 six stations in DKI Jakarta that measure PM.2.5 level at 6 areas. The ordinary kriging is one of spatial methods  that can be used to predict PM2.5 level in outside the existing stations, for example in the Pulogadung industrial area. This area was selected because there are many factories in this area that can increase levels of PM2.5 in the air. To predict the concentration of PM2.5 in one area could be done by calculating the surrounding PM2.5 concentrations that were not available to measure air quality. In study, we use mean an absolute percentage error ( MAPE ) value to evaluate Ordinary Kriging performance for predicting PM2.5 level in DKI Jakarta.

Keywords

Ordinary kriging Predict on PM2.5 levels DKI Jakarta

Article Details

How to Cite
Salsabilla, S. ., Fitri Syaharani, A., & Chamidah, N. (2023). Prediction of PM2.5 in DKI Jakarta Using Ordinary Kriging Method. Enthusiastic : International Journal of Applied Statistics and Data Science, 3(1), 48–58. https://doi.org/10.20885/enthusiastic.vol3.iss1.art5

References

  1. A.G. Simandjuntak ,”Pencemaran Udara,” Buletin Limbah, vol. 11, no. 1, pp. 34–40, 2007.
  2. R. Novirsa, U. Achmadi, and Fahmi, “Analisis Risiko Pajanan PM2,5 di Udara Ambien Siang Hari terhadap Masyarakat di Kawasan Industri Semen” Kesmas National Public Health Journal, vol. 7, no. 4, pp. 173–179, 2012, doi: http://dx.doi.org/10.21109/kesmas.v7i4.52.
  3. J.S. Brown, “Deposition of Particles,” in Comparative Biology of the Normal Lung, R.A. Parent, Ed., 2nd ed. MA, USA: Academic Press, 2015, ch. 27, pp. 513-536, doi: https://doi.org/10.1016/C2012-0-01154-4.
  4. R. Yendra and R. Risman, “Penerapan Metode Ordinary Kriging pada Pendugaan Kriminalitas di Kota Pekanbaru Riau,” Jurnal Sains Matematika dan Statistika, vol. 5, no. 1, pp. 13–22, 2019, doi: http://dx.doi.org/10.24014/jsms.v4i1.6701.
  5. I. Fauzi and E.S. Hariyadi, “Analisis Geostatistik dalam Menentukan Keseragaman Nilai Kepadatan Tanah Dasar,” Jurnal Teknik Sipil, vol. 25, no. 3, pp. 195–202, 2018, doi: https://doi.org/10.5614/jts.2018.25.3.4.
  6. N.A. Alfiana, “Metode Ordinary Kriging pada Geostatistika,” Bachelor thesis, Universitas Negeri Yogyakarta, Sleman, Indonesia, 2010.
  7. IQAir Staff Writers, “PM2.5,” IQAir.com. https://www.iqair.com/us/blog/air-quality/pm2-5 (accessed May 16, 2022).
  8. R. Mukhtar, E.H. Panjaitan, H. Wahyudi, M. Santoso, and S. Kurniawati, “Komponen Kimia PM2,5 dan PM10 di Udara Ambien di Serpong – Tangerang,” Jurnal Ecolab . Vol.7 , No. 1, pp. 1–7, 2013, doi: https://doi.org/10.20886/jklh.2013.7.1.1-7.
  9. A.A. Awali, H. Yasin, and R. Rahmawati, “Estimasi Kandungan Hasil Tambang Menggunakan Ordinary Indicator Kriging,” Jurnal Gaussian, vol. 2, no. 1, pp. 1–10, 2013, doi: https://doi.org/10.14710/j.gauss.2.1.1%20-%2010
  10. A.D.R. Bahtiyar, A. Hoyyi, and H. Yasin, “Ordinary Kriging Dalam Estimasi Curah Hujan di Kota Semaran,” Jurnal Gaussian, vol. 3, no. 2, pp. 152–153, 2014, doi: https://doi.org/10.14710/j.gauss.3.2.151%20-%20159.
  11. K.B. Rachmawati, I.A. Sukma, A. Triamartha, K.P. Dela, N. Chamidah, “Estimation of Dissolved Oxygen Using Spatial Analysis Based on Ordinary Kriging Method as Effort to Improve the Quality of Surabaya’s River Water,” Ecology, Environment and Conservation, vol. 25, pp. 62–66, 2019.
  12. D.W. Fitri, N. Afifah, S.M.D. Anggarani, N. Chamidah, “Prediction Concentration of PM2.5 in Surabaya Using Ordinary Kriging Method,” AIP Conference Proceedings, 2021, pp. 1–6, doi: https://doi.org/10.1063/5.0042284.
  13. S.A.D. Safitri, F.A. Putri, A.A. Belindha, N. Chamidah, “Co-Kriging Method Performance in Estimating the Number of COVID-19 Positive Confirmed Cases in East Java Province,” AIP Conference Proceedings, 2021, pp. 1–10, doi: https://doi.org/10.1063/5.0042286.
  14. G. Rozalia, H. Yasin, and D. Ispriyanti , “Penerapan Metode Ordinary Kriging pada Pendugaan Kadar No2 di Udara (Studi Kasus: Pencemaran Udara di Kota Semarang),” Jurnal Gaussian, vol. 5, no. 1, pp. 113–121, 2016, doi: https://doi.org/10.14710/j.gauss.5.1.113-121.
  15. S. Munadi, Pengantar Geostatistik. Jakarta, Indonesia: Universitas Indonesia, 2005.
  16. R. Hayami, Sunanto, and I. Oktaviandi, “Penerapan Metode Single Exponential Smoothing pada Prediksi Penjualan Bed Sheet,” Jurnal Computer Science and Information Technology (CoSciTech), vol. 2, no. 1, pp. 32–29, 2021, doi: https://doi.org/10.37859/coscitech.v2i1.2184.
  17. N.M.S. Fridayani, P.E.N. Kencana, and K.G. Sukarsa, “Perbandingan Interpolasi Spasial dengan Metode Ordinary dan Robust Kriging pada Data Spasial Berpencilan (Studi Kasus: Curah Hujan di Kabupaten Karangasem),” E-Jurnal Matematika, vol. 1, no. 1, pp. 68–74, 2012, doi: https://doi.org/10.24843/MTK.2012.v01.i01.p012.
  18. iQAir, https://www.iqair.com/id/ (accessed May 9, 2022).