Simple additive weighting method on intelligent agent for urban forest health monitoring

Abstract

Urban forest is a land where the trees grow cohesively and tightly in urban area, which is defined as urban forest by the competent authority. The main functions of urban forest are to keep and restore the micro climate and aesthetic value; keep water; create balance and harmony of the urban physical environment, also support the biodiversity conservation of Indonesia. Its making keeps the sustainability of the forest which becomes important. Forest health monitoring is one of ways to keep urban forest sustainable. It is used to determine the precaution that can be done. This study aims to provide the analysis and design of intelligent agent as a decision maker in the urban forest health monitoring, with the utilization of Simple Additive Weighting (SAW) method. The result is the model of intelligent agents who can assist in determining the health level of urban forest.