IMPLEMENTATION OF ARMA MODEL FOR BENGAWAN SOLO RIVER WATER LEVEL AT JURUG MONITORING POST

Abstract

The amount of annual rainfall in the Bengawan Solo watershed causes high water flow (water discharge) in several rivers. In addition, high flow rates significantly increased the water surface level at some observation sites. The Bengawan Solo River burst its banks in November 2016, causing flooding in several areas in eastern Solo. At that time, the river stage at the Jurug monitoring post passed ten. Therefore, a flood early warning system would be useful for predicting water levels in this context. Every day, one post on the Bengawan Solo River measures the water level. The time series data used in this study is the water level. Autoregressive Moving Average (ARMA) is a predictive method for measuring time set data. The assumption of homoscedasticity or constant error variance is used in this model. However, the study will use the ARMA model if the variance changes randomly. The study used 60 pieces of data from January to February 2018. This study can directly use ARMA because the data results are stationary based on ADF value 0.0036. After the first pause, the ACF and PACF are disconnected based on the correlogram pattern. This shows that the water level of the Bengawan Solo River in that period can appear on the Autoregressive Moving Average with orders p = 1 and q = 1 ARMA(1,1). Thus, the total average residue is 0.0668384, so the short error is 6.68384%.

Keywords

• autoregressive moving average (arma)
• jurug monitoring post
• time series analysis
• water level