Smart City Application: Community Survey System of Urban Comfort Level

Abstract

Based on the projected increase in urban population in Indonesia released by the Ministry of PUPR and Bappenas in 2017 that there was a significant increase in urbanization, which is estimated that in 2015-2035 the population in urban areas will exceed the population in rural areas (66.6% of the population urban and 33.4% rural population). Increasing the number of the urban population needs to get proper handling from the government. If not, it will trigger the emergence of various urban problems ranging from the physical city to the problems that will have an impact on the reduced level of comfort in life in the region. Based on this, it is necessary for the participation of city dwellers in playing the role of planners, actors, and supervisors of city development. This research work develops a framework which uses fuzzy Inference System to calculate urban comfort level, starting from a questionnaire-based survey. There are seven input variables used to produce an output of urban comfort level. Based on the stages of using the Mamdani Model Fuzzy Inference Logic System starting from the formation of the fuzzy set, the application of the impulse function, the composition of the rules to the process of affirmation (defuzzification), it can be proven that there is a correlation between the input variables so that it can determine the output of urban comfort level results. The outcomes help the city government in making public policy on city development.