Open AccessVector Autoregressive (VAR) Model for Rain-Fall Forecasting in West Java Indonesia at the Peak of the Rainy Season
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1054.0782s719
Subject(s) - wet season , autoregressive model , java , time series , geography , statistics , environmental science , mathematics , meteorology , cartography , computer science , programming language
Rain is a natural event that occurs in every region. Rainfall intensity in several regions that are close together indicates the same rainfall pat-tern each year, especially during the peak of the rainy season. Time series modeling that uses more than one variable can be used to see the relationship between the rainfall patterns. Vector Autoregressive (VAR) is a multivariate time series method that is used to see the relation-ships between variables and to forecast. The data that is used in this study are monthly rainfall data at the peak of the rainy season (December, January, February) in three locations in West Java, namely Bandung City, Cimahi City, and West Bandung Regency with a period of time from December 1981 - February 2017. Based on the results of the analysis, it shows the similarity of rainfall patterns from the three locations based on plot data and high correlation values between locations. The appropriate VAR model is VAR(3) based on the smallest AIC value and has an average MAPE value 18,817 percent.