ANALISIS DIAGNOSTIK VARIABEL CUACA UNTUK ESTIMASI POLA CURAH HUJAN DI MEDAN MENGGUNAKAN MODEL BAYESIAN VECTOR AUTOREGRESSIVE

Abstract

The territory of Indonesia is located in a strategic position in the tropics. Indonesia is in a position where the equator passes, making it vulnerable to changes in weather and climate. Big cities are increasingly facing many global challenges, so that the effects of climate change are causing urban areas to become more vulnerable to disasters. The city of Medan is one of the big cities that has been recognized as having different characteristics from the surrounding climate, which still has quite a lot of natural elements. Various community activities in Medan City can change the composition of the atmosphere which causes changes in the characteristics of the microclimate which will affect the weather and climate. Weather and climate have a dynamic relationship with other weather elements such as air humidity, air temperature and rainfall. Weather and climate patterns often do not match the pattern they should and are difficult to predict. The main elements of weather are temperature and rainfall, knowing the temperature and rainfall of an area can be used as material to describe the weather in that area. In expressing rainfall in an area, the relationship between air humidity, air temperature and wind direction and speed is very influential. Knowing the pattern of rainfall is very important to do in several activities. So that a diagnostic analysis of weather variables is needed to estimate rainfall patterns in the city of Medan using the bayesian vector autoregressive (BVAR) model. The estimation results using the Bayesian Vector Autoregressive (BVAR) model for Medan City found that the highest rainfall occurred in September at 571.87 mm and the lowest occurred in January at 54.59 mm with a method accuracy rate of 4.75% which indicates that the use of the BVAR method in estimation is very accurate

Keywords

• bayesian vector autoregressive
• curah hujan
• rainfall