PERAMALAN KUALITAS UDARA KOTA BANDUNG DENGAN METODE FUZZY MAMDANI DAN ALGORITMA GENETIKA-FUZZY TIME SERIES - Fidela Neysa Kaulika; Kartika Yulianti; Entit Puspita; Rini Marwati (Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat, 2025)
Air quality is an important element that has a significant impact on human health and comfort as well as environmental sustainability. Bandung City, as one of the major cities in Indonesia, has experienced a significant increase in the volume of motorized vehicles and the number of industrial plants, which has led to a decrease in air quality. This research aims to forecast air quality in Bandung City using the fuzzy time series method optimized by a genetic algorithm. The parameters that determine air quality used include PM2.5 concentration, PM10 concentration, and NO2 concentration. In this research, fuzzy logic is applied to process the historical data of these parameters into output data in the form of air quality estimation by forming a Fuzzy Inference System (FIS) using fuzzy Mamdani. The results showed that the combined genetic algorithm and fuzzy time series method produced more accurate air quality forecasting than the fuzzy time series method alone, with a Mean Absolute Percentage Error (MAPE) accuracy rate of 8,52%, which is included in the excellent and successful forecasting category