Peramalan Curah Hujan Di Kota Samarinda Menggunakan Vector Error Correction Model

Abstract

The Vector Error Correction Model (VECM) was one of the multivariate time series models that was a development of the Vector Autoregressive (VAR). VECM could be used to forecast non-stationary time series variables that had cointegration relationships. This study used monthly data of rainfall, minimum air temperature, and maximum air humidity variables from January 2015 to December 2023 to form the VECM model. The purpose of this study was to obtain a VECM model for rainfall in the city of Samarinda and to forecast rainfall in the city of Samarinda using VECM. The results of the study showed that the VECM model that formed was VECM(1) with two cointegration relationships. The rainfall forecasted results with VECM(1) indicated a downward trend until April 2024 and a horizontal pattern from May to December, with the highest rainfall in January at 214 mm and the lowest rainfall in April at 182.5 mm. The forecasted results ranged between 180-300 mm, which was categorized as moderate, with forecasting accuracy using a MAPE value of 32.369%, which was considered quite good.