Vector Autoregressive (VAR) modeling for weather forecasting in Madura

Ira Yudistira; Kuzair; Faisol

doi:10.30762/f_m.v7i2.3486

Authors

Ira Yudistira Department of Mathematics, Universitas Islam Madura, Pamekasan, Indonesia
Kuzair Department of Mathematics, Universitas Islam Madura, Pamekasan, Indonesia
Faisol Department of Mathematics, Universitas Islam Madura, Pamekasan, Indonesia

DOI:

https://doi.org/10.30762/f_m.v7i2.3486

Keywords:

Air Temperature, Air Humidity, Forecasting, Vector Autoregressive

Abstract

Air temperature, air humidity and sunlight are interconnected weather elements. The high and low intensity of solar radiation affects air temperature, while air temperature affects air humidity. These three elements have an important role in global climate change and human activities on earth. In the agricultural sector, air temperature, air humidity and sunlight influence plant growth and development. These three elements also influence the water supply on earth. Information about these three weather elements is very important for Madura, where the majority of the population are farmers and planters, to determine more effective planting patterns. This research aims to create a model that can predict these three elements so that Madurese farmers and planters can plan planting patterns. A forecasting model that is able to handle predictions of several correlated variables is the Vector Autoregressive (VAR) model. The forecasting model obtained in this research is the VAR(5) model. MAPE for air temperature shows accurate forecasting results with a value of 2.3186%, while for air humidity and solar radiation shows quite accurate forecasting results with values of 29.6125% and 36.4231% respectively.

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