Open AccessAn approach for passengers forecasting using Fuzzy Time Series
Author(s) -
Undang Syaripudin,
Wildan Budiawan Zulfikar,
Wisnu Uriawan,
Rifqi Ardian Nugraha
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1098/3/032053
Subject(s) - time series , series (stratigraphy) , operations research , fuzzy logic , computer science , transport engineering , econometrics , statistics , mathematics , engineering , artificial intelligence , paleontology , biology
At certain times the number of passengers is very difficult to predict. There was a time when the number of passengers occurred a very significant surge. However, there are times when the number of passengers is drastically reduced. This is caused by many factors including time including the holiday season, holidays, and so on. As for other factors such as natural disasters, endemic diseases, and others. The number of passengers must be proportional to the number of vehicles that have been prepared. The company must consider the condition of the vehicle and also the physical condition of the driver. The aim of this study is to conduct passenger forecasting on a coming day. The methodology used is Fuzzy Time Series. The result of the experiment shows that this model has the accuracy of the difference between predictions with real data using PE which is equal to 34.6%.