Spatial Decision Support System for School Sitting

School building is a long term investment that always involves huge capital. Although school building has always been given top priority in the Malaysia Plan series, the number of existing schools is still inadequate. The present system of school planning is inefficient because it has neglected the spatial factor which is part of very important components in educational planning. Poorly planned schools will lead to obsolescence and once this happens, the schools in the area either have to be remodeled or be replaced. Despite the importance of school planning, not much information are available that deals with spatially-based school planning as a complete process. Most of them are written by planners from developed countries which have been found unsuitable for developing countries such as Malaysia because of the differences in policy and focus. Therefore there is an urgent need to develop a Spatial Decision Support System for school planning that suits the local setting. The objectives of this system are first to identify parameters for the proposed study, establish a model to optimize the school system efficiency, identify the most suitable location for a new school and then redraw the attendance boundary based on the optimization of school capacity and student distribution. To achieve this, GIS analysis is combined with other tools such as Multiple Criteria Analysis, Analytical Hierarchy Process, Location- Allocation Modeling and Gravity Model. Based on the diagnosis, three possible solutions are suggested, followed by discussions of the advantages and disadvantages of each scenario. The results generated by the system are very encouraging because it has shown that schooling system can be improved significantly while satisfying both the shortest distance constraint and also the school capacity constraint. The study has shown that this GIS-based system is able to fulfill all the objectives of this study. Through readings and research, all parameters and constraints have been identified as inputs for the system. Using these parameters, this system is able to classify schools based on the critical needs as well as identifying the most suitable region for providing new schools or relocation of the existing schools. Lastly, the system is able to show alternatives towards making the best decision by providing simulations based on many possibilities. This model also has the potential to be extended for other educational planning areas, for example the allocation of teaching personnel and the distribution of educational resources. As a conclusion, this GIS-based system, combined with educational data can be a very important tool for educational planning.

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