Sustainable analysis of affordable housing building in east java (study case: Pasuruan)

One of the issues caused by the high growth of the urban population is the increasing demand for housing. In several cases, the government does this by inviting other parties' involvement, especially the private sector to provide both means and facilities. However, these demands didn't correspond to the availability of either land or affordable housing, especially for people with lower middle income. To create secure, quality, and affordable housing for Low-Income Communities (LIC), developers are expected to deepen their understanding of the sustainability idea. This study aims to create an assessment model of sustainable affordable housing that covers economic, environmental, and social aspects. This study utilized the method of the Adaptive Neuro-Fuzzy Inference System to conduct an affordable housing analysis based on sustainable variables by displaying a ranking priority order. Continuous variables are assembled and will be confirmed through a questionnaire on the experts, which is later processed by using the software of the Adaptive Neuro-Fuzzy Inference System. An Adaptive Neuro-Fuzzy Inference System (ANFIS), a hybrid of a neural network and fuzzy theory, was utilized to determine whether cheap housing was sustainable. The ANFIS system was identified using coefficient of correlation (R) and root mean square error (RMSE), showing an ideal and effective outcome.