Variable precision rough set model for attribute selection on environment impact dataset

(1) * Ani Apriani Mail (Department of Geology Engineering, STTNAS, Yogyakarta, Indonesia)
(2) Iwan Tri Riyadi Yanto Mail (Department of Information System, Universitas Ahmad Dahlan, Indonesia)
(3) Septiana Fathurrohmah Mail (Department of Urban and Regional Planning, STTNAS, Yogyakarta, Indonesia)
(4) Sri Haryatmi Mail (Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
(5) Danardono Danardono Mail (Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia)
*corresponding author


The investigation of environment impact have important role to development of a city. The application of the artificial intelligence in form of computational models can be used to analyze the data. One of them is rough set theory. The utilization of data clustering method, which is a part of rough set theory, could provide a meaningful contribution on the decision making process. The application of this method could come in term of selecting the attribute of environment impact. This paper examine the application of variable precision rough set model for selecting attribute of environment impact. This mean of minimum error classification based approach is applied to a survey dataset by utilizing variable precision of attributes. This paper demonstrates the utilization of variable precision rough set model to select the most important impact of regional development. Based on the experiment, The availability of public open space, social organization and culture, migration and rate of employment are selected as a dominant attributes. It can be contributed on the policy design process, in term of formulating a proper intervention for enhancing the quality of social environment.


Environment; VPRS; Error classification; Attribute selection



Article metrics

Abstract views : 484 | PDF views : 143




Full Text



[1] 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:

[2] 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:

[3] 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:

[4] 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:

[5] L. M. Ferri and M. Pedrini, “Socially and environmentally responsible purchasing: Comparing the impacts on buying firm’s financial performance, competitiveness and risk,” J. Clean. Prod., vol. 174, pp. 880–888, 2018, doi:

[6] J. K. Owusu-Ansah and F. Atta-Boateng, “The spatial expression of physical development controls in a fast growing Ghanaian city,” Land use policy, vol. 54, pp. 147–157, 2016, doi:

[7] 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:

[8] 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:

[9] S. Ullrich-French, A. N. Cole, and A. K. Montgomery, “Evaluation development for a physical activity positive youth development program for girls,” Eval. Program Plann., vol. 55, pp. 67–76, 2016, doi:

[10] A. K. M. Tarigan, D. A. A. Samsura, S. Sagala, and A. V. M. Pencawan, “Medan City: Development and governance under the decentralisation era,” Cities, vol. 71, no. July, pp. 135–146, 2017, doi:

[11] A. K. M. Tarigan, D. A. A. Samsura, S. Sagala, and R. Wimbardana, “Balikpapan: Urban planning and development in anticipation of the post-oil industry era,” Cities, vol. 60, pp. 246–259, 2017, doi:

[12] W. Li, C. Wu, and S. Zang, “Modeling urban land use conversion of Daqing City, China: a comparative analysis of ‘top-down’ and ‘bottom-up’ approaches,” Stoch. Environ. Res. Risk Assess., vol. 28, no. 4, pp. 817–828, May 2014, doi:

[13] T. Woldai and A. G. G. Fabbri, “The Impact of Mining on The Environment,” in Deposit and Geoenvironmental Models for Resource Exploitation and Environmental Security, 2002, pp. 345–364, doi:

[14] Hamdani and R. Wardoyo, “A Review on fuzzy multi-criteria decision making land clearing for oil palm plantation,” Int. J. Adv. Intell. Informatics, vol. 1, no. 2, pp. 75–83, 2015,

[15] M. Muhajir and B. R. Efanna, “Association Rule Algorithm Sequential Pattern Discovery using Equivalent Classes ( SPADE ) to Analyze the Genesis Pattern of Landslides in Indonesia,” Int. J. Adv. Intell. Informatics, vol. 1, no. 3, pp. 158–164, 2015, doi:

[16] D. Ismi, S. Panchoo, and M. Murinto, “K-means clustering based filter feature selection on high dimensional data,” Int. J. Adv. Intell. Informatics, vol. 2, no. 1, pp. 38–45, 2016, doi:

[17] I. T. R. Yanto, R. R. Saedudin, D. Hartama, and T. Herawan, Clustering based on classification quality (CCQ), 2017, vol. 549 AISC, doi:

[18] W. Ziarko, “Variable precision rough set model,” J. Comput. Syst. Sci., vol. 46, no. 1, pp. 39–59, 1993, doi:

[19] Z. Pawlak, “Rough sets,” Int. J. Comput. Inf. Sci., vol. 11, no. 5, pp. 341–356, 1982, doi:

[20] Z. Pawlak and A. Skowron, “Rudiments of rough sets,” Inf. Sci. (Ny)., vol. 177, no. 1, pp. 3–27, Jan. 2007, doi:

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

International Journal of Advances in Intelligent Informatics
ISSN 2442-6571  (print) | 2548-3161 (online)
Organized by Informatics Department - Universitas Ahmad Dahlan , and UTM Big Data Centre - Universiti Teknologi Malaysia
Published by Universitas Ahmad Dahlan
W :
E :, (paper handling issues), (publication issues)

View IJAIN Stats

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0