Vector Autoregressive (VAR) for Rainfall Prediction

Authors

  • Tita Rosita Lecturer, Department of Statistics, Polytechnic of AKA Bogor, INDONESIA
  • Zaekhan Assistant Professor, Graduate Program in Economics, Universitas Indonesia, INDONESIA
  • Rachmawati Dwi Estuningsih Lecturer, Department of Statistics, Polytechnic of AKA Bogor, INDONESIA

Keywords:

Vector Auto Regressive (VAR), Circular Data, Rainfall

Abstract

Weather and climate information is useful in a variety of areas including agriculture, tourism, transportation both land, sea and air. For that, up to date weather and climate data and its forecasting are essential. This study aims to create rainfall modeling with Vector Auto Regressive (VAR) using circular data and linear data. The data used comes from the station climatology Darmaga Bogor period 2006-2017. The VAR model (2) of the rainfall variables in the t-month is affected by the t-1 moisture air moisture, the t-2 moisture air and the air temperature at t-2. This VAR model (2) is used to forecast the next period. The mean absolute percentage error (MAPE) VAR (2) obtained was 42.18. The novelty of the study is (1) VAR modeling for rainfall prediction, (2) Use of circular data for wind direction data.

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Published

2018-04-30

How to Cite

Tita Rosita, Zaekhan, & Rachmawati Dwi Estuningsih. (2018). Vector Autoregressive (VAR) for Rainfall Prediction. International Journal of Engineering and Management Research, 8(2), 96–102. Retrieved from https://ijemr.vandanapublications.com/index.php/ijemr/article/view/685

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