Fast Clustering Environment Impact using Multi Soft Set Based on Multivariate Distribution

Iwan Tri Yanto - Department of Information Systems, University of Ahmad Dahlan, Yogyakarta, Indonesia
Ani Apriani - Faculty of Technology Mineral, Institut Teknologi Nasional Yogyakarta, Yogyakarta, Indonesia
Rahmat Hidayat - Department of Information Technology, Politeknik Negeri Padang, Padang, West Sumatera, Indonesia
Mustafa Mat Deris - Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia
Norhalina Senan - Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia


Citation Format:



DOI: http://dx.doi.org/10.30630/joiv.5.3.628

Abstract


Every development activity is always related to human or community aspects. This can also lead to changes in the characteristics of the community. The community's increasing awareness and critical attitude need to be accommodated to avoid the emergence of social conflicts in the future. This research is to find out how the public perception about the impact of development on the environment. Two methods are used, i.e., MDA (Maximum Dependency Attribute) and MSMD (the Multi soft set multivariate distribution function). The MDA is to determine the most influential attribute and the Multi soft set multivariate distribution function (MSMD) is to group the selected data into classes with similar characteristics. This will help the police producer plan the right mediation and take quick activity to make strides in the quality of the social environment. The experiment conducted level of impact based on the clustering results with the greatest number of member clusters is cluster 1 (very low impact) with 32.25 % of total data following cluster 5 (Very High impact) with 24.25 % of total data. The experiment obtains the level of impact based on the clustering results. The greatest number of member clusters is cluster 1 (extremely low impact) with 32.25 % of total data following cluster 5 (Very High impact) with 24.25 % of total data. The scatter area impact is spread at districts 6, 7, 10, 11, the most of very high impact and districts 1,2,3,4,5,8 the lowest impact. 


Keywords


Environment impact MDA; clustering; multi soft set; multinomial distribution.

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References


P. Clavel and R. Young, “‘Civics’: Patrick Geddes’s theory of city development,” Landsc. Urban Plan., vol. 166, no. June, pp. 37–42, 2017, doi: 10.1016/j.landurbplan.2017.06.017.

A. Kumari and A. K. Sharma, “Physical & social infrastructure in India & its relationship with economic development,” World Dev. Perspect., vol. 5, pp. 30–33, 2017, doi: 10.1016/j.wdp.2017.02.005.

P. Ashcroft and L. Murphy Smith, “Impact of environmental regulation on financial reporting of pollution activity: A comparative study of U.S. and Canadian firms,” Res. Account. Regul., vol. 20, pp. 127–153, Jan. 2008, doi: 10.1016/S1052-0457(07)00207-X.

J. K. Woo, D. S. H. Moon, and J. S. L. Lam, “The impact of environmental policy on ports and the associated economic opportunities,” Transp. Res. Part A Policy Pract., no. xxxx, pp. 0–1, 2017, doi: 10.1016/j.tra.2017.09.001.

P. Ashcroft and L. Murphy Smith, “Impact of environmental regulation on financial reporting of pollution activity: A comparative study of U.S. and Canadian firms,” Res. Account. Regul., vol. 20, pp. 127–153, 2008, doi: https://doi.org/10.1016/S1052-0457(07)00207-X.

K. Howard and R. Gerber, “Impacts of urban areas and urban growth on groundwater in the Great Lakes Basin of North America,” J. Great Lakes Res., vol. 44, no. 1, pp. 1–13, 2018, doi: https://doi.org/10.1016/j.jglr.2017.11.012.

A. R. Shahtahmassebi et al., “How do modern transportation projects impact on development of impervious surfaces via new urban area and urban intensification? Evidence from Hangzhou Bay Bridge, China,” Land use policy, vol. 77, pp. 479–497, 2018, doi: https://doi.org/10.1016/j.landusepol.2018.05.059.

P. K. Yogyakarta, “Dampak Pertumbuhan Hotel Terhadap Perubahan Karakteristik Perwilayahan Kota Yogyakarta Tika Ainunnisa Fitria,” vol. 10, pp. 52–57, 2016.

M. T. Dugan, E. H. Turner, M. A. Thompson, and S. M. Murray, “Measuring the financial impact of environmental regulations on the trucking industry,” Res. Account. Regul., vol. 29, no. 2, pp. 152–158, 2017, doi: 10.1016/j.racreg.2017.09.007.

C. Mary Schooling, E. W. L. Lau, K. Y. K. Tin, and G. M. Leung, “Social disparities and cause-specific mortality during economic development,” Soc. Sci. Med., vol. 70, no. 10, pp. 1550–1557, 2010, doi: 10.1016/j.socscimed.2010.01.015.

T. Woldai and A. G. Fabbri, “The Impact of Mining on The Environment,” in Deposit and Geoenvironmental Models for Resource Exploitation and Environmental Security, A. G. Fabbri, G. Gaál, and R. B. McCammon, Eds. Dordrecht: Springer Netherlands, 2002, pp. 345–364.

I. T. R. Yanto, “Minimum error classification clustering,” Int. J. Softw. Eng. its Appl., vol. 7, no. 5, pp. 221–232, 2013, doi: 10.14257/ijseia.2013.7.5.20.

I. T. R. Yanto, A. Rahman, and Y. Saaadi, “Soft Maximal Association Rule for web user mining,” 2017, doi: 10.1109/ICSITech.2016.7852659.

I. T. R. Yanto, E. Sutoyo, A. Apriani, and O. Verdiansyah, “Fuzzy Soft

Set for Rock Igneous Clasification,” 2019, doi: 10.1109/SAIN.2018.8673383.

M. Muhajir and B. Rian, “Association Rule Algorithm Sequential Pattern Discovery using Equivalent Classes ( SPADE ) to Analyze the Genesis Pattern of Landslides in Indonesia,” vol. 1, no. 3, pp. 158–164, 2015.

N. Senan, R. Ibrahim, N. M. Nawi, I. T. R. Yanto, and T. Herawan, “Soft Set Theory for Feature Selection of Traditional Malay Musical Instrument Sounds,” 2010, pp. 253–260.

I. T. R. Yanto, M. A. Ismail, and T. Herawan, “A modified Fuzzy k-Partition based on indiscernibility relation for categorical data clustering,” Eng. Appl. Artif. Intell., vol. 53, pp. 41–52, Aug. 2016, doi: 10.1016/j.engappai.2016.01.026.

T. Herawan, M. M. Deris, and J. H. Abawajy, “A rough set approach for selecting clustering attribute,” Knowledge-Based Syst., vol. 23, no. 3, pp. 220–231, Apr. 2010, doi: 10.1016/j.knosys.2009.12.003.

N. Senan, R. Ibrahim, N. Mohd Nawi, I. T. R. Yanto, and T. Herawan, Rough set approach for attributes selection of traditional Malay musical instruments sounds classification, vol. 151 CCIS, no. PART 2. 2011.

D. W. Jacob, M. F. M. Fudzee, M. A. Salamat, R. R. Saedudin, I. T. R. Yanto, and T. Herawan, An application of rough set theory for clustering performance expectancy of indonesian e-government dataset, vol. 549 AISC. 2017.

T. Herawan, M. M. Deris, and J. H. Abawajy, “Matrices Representation of Multi Soft-Sets and Its Application,” in Computational Science and Its Applications -- ICCSA 2010: International Conference, Fukuoka, Japan, March 23-26, 2010, Proceedings, Part III, D. Taniar, O. Gervasi, B. Murgante, E. Pardede, and B. O. Apduhan, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 201–214.




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