Neuro-Fuzzy for Traffic Volume Forecasting of National Road III Jember Banyuwangi KM 252 - Muhammad Shofwan Donny Cahyono; Agustinus Angkoso (Litbang Pemas - Universitas Islam Lamongan, 2021)
Traffic congestion is one of the prevalent phenomena in Indonesia, especially in big cities. There are a variety of factors causing congestion in the city, including the expansion of existing infrastructure, the large number of residents in the area, and the disparity between the growth of motor vehicles and highways. By careful transport planning, this can be fixed. The estimation of traffic volume is one strategy to see how much road growth is to offset vehicle volume growth to prevent congestion. This study tries to estimate the traffic volume of National Road III Jember Banyuwangi KM 252 motorized 2-wheeled vehicles passing by. The data used were obtained from 24 hours observation for 7 days. Using the Neuro-Fuzzy method which applies 1 day out of 7 days as testing data, and obtaining the average error is 13.2747%. This average error shows that the error rate that occurs is 5% of all errors. Neuro-Fuzzy can forecast the traffic volume of 2-wheeled motorized vehicles reasonably well.