Perbandingan Pengelompokan pada Wilayah Berdasarkan Tingkat Kerusakan Lingkungan di Indonesia
DOI:
https://doi.org/10.21831/pspmm.v8i2.278Keywords:
Lingkungan, analisis klaster, klaster ensemble, klaster hirarkiAbstract
Abstrak—Kerusakan lingkungan adalah salah satu perhatian dunia saat ini. Dikarenakan kerusakan lingkungan akan memiliki dampak negatif bagi umat manusia. Oleh karena itu untuk memberikan gambaran mengenai daerah yang butuh perhatian lebih dalam masalah kerusakan lingkungan di Indonesia, sehingga diperlukan pengelompokan. Sehingga pada penelitian ini menggunakan metode hierarki, k-means cluster, dan cluster ensemble untuk mengelompokan wilayah. Hasil analisis menunjukkan bahwa cluster ensemble memberikan hasil yang lebih baik dalam pengelompokan wilayah. Pada penelitian ini digunakan data dari 34 provinsi dengan menggunakan variabel indeks kualitas udara (IKU), indeks kualitas air (IKA), kualitas tutupan lahan (IKTL), dan sampah terkelola.References
BPS. (2018). Statistik Potensi Desa Indonesia 2018. Badan Pusat Statistik.
Chiu, D. S., & Talhouk, A. (2018). diceR: an R package for class discovery using an ensemble driven approach. BMC Bioinformatics, 19(1), 11. https://doi.org/10.1186/s12859-017-1996-y
Croitoru, L., & Sarraf, M. (Eds.). (2010). The Cost of Environmental Degradation. The World Bank. https://doi.org/10.1596/978-0-8213-8318-6
Data world bank. (2011). CO2 emissions (metric tons per capita). World Bank. https://data.worldbank.org/indicator/EN.ATM.CO2E.PC?locations=ID
Gujarati, D. N. (2003). Basic Econometrics. In The Economic Journal. Gary Burke. https://doi.org/10.2307/2230043
ILO. (2018). The Employment Impact of Climate Change Adaptation.Input Document for
the G20 Climate Sustainability Working Group (p. 40). Retrieved from https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/publication/wcms_645572.pdf
Johson RA, Winchern DW. 2007. Applied Multivariate Statistical Analysis.New Jersey: Prentice Hall.
Landrigan, P. J., Fuller, R., Acosta, N. J. R., Adeyi, O., Arnold, R., Basu, N. (Nil), Baldé, A. B., Bertollini, R., Bose-O’Reilly, S., Boufford, J. I., Breysse, P. N., Chiles, T., Mahidol, C., Coll-Seck, A. M., Cropper, M. L., Fobil, J., Fuster, V., Greenstone, M., Haines, A., … Zhong, M. (2018). The Lancet Commission on pollution and health. The Lancet, 391(10119), 462–512. https://doi.org/10.1016/S0140-6736(17)32345-0
Lelieveld, J., Klingmüller, K., Pozzer, A., Burnett, R. T., Haines, A., & Ramanathan, V. (2019). Effects of fossil fuel and total anthropogenic emission removal on public health and climate. Proceedings of the National Academy of Sciences, 116(15), 7192–7197. https://doi.org/10.1073/pnas.1819989116
Liu, Y., Li, Z., Xiong, H., Gao, X., & Wu, J. (2010). Understanding of Internal Clustering Validation Measures. 2010 IEEE International Conference on Data Mining, 911–916. https://doi.org/10.1109/ICDM.2010.35
Mattjik AA, Sumertajaya IM. 2011. Sidik Peubah Ganda dengan Menggunakan SAS. Wibawa GNA, Hadi AF, editor. Bogor (ID): IPB Press
Nicolas Maitre, Guillermo Montt and Catherine Saget, with additional contributions by Christoph Ernst, María Teresa Gutiérrez, Takaaki Kizu, Tahmina Karimova, M., & Lieuw-Kie-Song, and M. T. (n.d.). The employment impact of climate change adaptation Input Document for the G20 Climate Sustainability Working Group.
Noor N. M., Yahaya A. S., Ramli N. A., Luca F. A., Abdullah M. M. A., Sandu A. V. (2015),
Variation of Air Pollutant (Particulate Matter - PM10) in Malaysia. Study in the Southwest Coast of Peninsular Malaysia, Revista de Chimie 66(9): 1443-1447.
Solarin, S. A. (2019). Convergence in CO 2 emissions, carbon footprint and ecological footprint: evidence from OECD countries. Environmental Science and Pollution Research, 26(6), 6167–6181. https://doi.org/10.1007/s11356-018-3993-8
Strehl A,Gosh J. 2012. A Knowledge Reuse Framework for Combining Partitionings. The Journal of Machine learning Research. 3(1):583-6
World Bank Group, & IHME. (2016). The cost of air pollution: Strengthening the Economic
Case for Action. The World Bank and Institute for Health Metrics and Evaluation University of Washington, Seattle (pp. 1–102). Retrieved from http://www.tandfonline.com/doi/abs/10.1080/000368497326688#.Va9xXPnQjVI
