Fuzzy-Based Decision Support Model for Assessing Green Building Performance
DOI:
https://doi.org/10.21512/commit.v18i2.9797Keywords:
Decision Support Model, Fuzzy Logic, Green BuildingAbstract
Global warming is currently a major environmental issue that is capable of causing unpredictable climate changes. The phenomenon is due to the accumulation of gases and carbon dioxide in the earth’s atmosphere, partly attributed to building operation and construction. The Green Building Rating System (GBRS) is developed to assess and measure the level of green building practices to address this problem. The assessments have typically been conducted using conventional methods that require parameters to meet specific criteria. However, certain parameter values cannot be calculated using objective methods, such as bias, time series, and distance values. The existence of these challenges leads to the development and integration of the Decision Support Model (DSM) into the GBRS in the research. The DSM uses a mathematical model, Tsukamoto Fuzzy Inference System (FIS), and conventional methods to handle the parameter values. Moreover, data related to the parameters are collected and analyzed quantitatively. As a result, the DSM-GBRS model is successfully implemented with two findings. First, there are 83 parameters, related to policy, retrofit, construction, and utilization aspects based on Peraturan Menteri Pekerjaan Umum dan Perumahan Rakyat Nomor 21 Tahun 2021. Second, the model provides precise decision values by splitting the treatment into four types: conventional, Fuzzy logic, slope, and Euclidean distance to ensure a comprehensive assessment of green building performance.
Plum Analytics
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