Comparison Of MOORA and COPRAS Methods Based on Geographic Information System For Determining Potential Zone of Pasir Batu Mining

Abstract

Population growth has an impact on increasing living needs, including the need for building materials. The high demand for building materials will spur the increase in mining activities, especially in Kediri Regency as the largest Pasir Batu producing district in East Java Province. On the other hand this industry also creates environmental changes that threaten the sustainability of environmental functions and the socio-cultural life. This was compounded by the lack of careful consideration in assessing the potential area for mining exploration by Pasir Batu. This paper proposes to determine the potential zone of Batu Pasir mining based on the specified criteria. Criteria are based on the definition of Mining and Exploration in UU Republik Indonesia 4/2009. The criteria used are grouped into 3 categories. First, natural factors consist of morphology, lithology, hydrology, vegetation and wild nature. Second, man-made factors include safe distance from the main road, settlement distance and population density. Third, aesthetic factors consist of natural elements and tourist locations. The research method used is the integration of Geographic Information System (GIS) with the calculation of Multi Criteria Decision Making (MCDM) using the AHP (Analytical Hierarchy Process) method, Multi-Objective Optimization by Ratio Analysis (MOORA) and Complex Proportional Assessment (COPRAS). GIS is used for data integration so that the determination of zoning is visual and easier to understand. The AHP method is used to determine the weighting of each criterion. The results of weighting the criteria serve as the basis for ranking alternative locations between the MOORA and COPRAS methods. The final outcome shows that two methods have a slightly different weight rank, but the COPRAS method is more stable and complex. The judgement is very influential in the selection of criteria and deliberate hierarchy to determine the significance of each criterion on the weighting of criteria.