Open AccessPriority Modeling for Public Urban Park Development in Feasible Locations using GIS, Intuitionistic Fuzzy AHP, and Fuzzy TOPSIS
Author(s) -
Arif Wicaksono
Publication year - 2021
Publication title -
jurnal rekayasa elektrika
Language(s) - English
Resource type - Journals
eISSN - 2252-620X
pISSN - 1412-4785
DOI - 10.17529/jre.v17i4.23138
Subject(s) - analytic hierarchy process , topsis , fuzzy logic , computer science , vagueness , geographic information system , geography , ideal solution , operations research , mathematics , data mining , artificial intelligence , cartography , physics , thermodynamics
As feasible locations of public urban park in Bogor Municipality have been acquired in a previous study, decision makers are urgently needed to be informed on which locations should be prioritized for public urban park (PUP) development. Therefore, this study aggregates four multi-spatial criteria for PUP development priority modeling, namely distance to slum neighborhood, accessibility, slope, and land value. These four criteria in form of vector datasets were weighted using intuitionistic fuzzy analytical hierarchy process (IF-AHP) to consider the hesitancy, vagueness, and fuzziness might arise from experts’ judgement as well as from multi-spatial data processing. Resulted criteria weights from IF-AHP show that accessibility weight 0.261, land value weight 0.259, distance to slum weight 0.255, and slope weight 0.225, respectively. Criteria weights were inputted into fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) and geographic information system (GIS) to rank location priority. Results from fuzzy TOPSIS show that very high priority class which has the biggest CCi values range (0.654-0.76) provides 0.14 km2 area of feasible PUP development scattered in 10 locations. The biggest area for feasible PUP development is generated by medium priority class (CCi values 0.439-0.546) in 26 locations and approximately area of 0.38 km2.