Development of ARIMA technique in determining the ocean climate prediction skills for pre-service teacher

Abstract

The lack of community understanding of the predictions of the ocean climate is key to addressing the impacts and crisis of the ocean climate. The aims of this study is to explain the stages of ocean climate prediction skills using the ARIMA technique for pre service teacher students as beginner learners and provide solutions to build a conscious and responsive attitude to the ocean climate. The data used is Sea Surface Temperature (SST) Niǹo 3.4, analysis the stages of the Autoregressive Integrated Moving Average (ARIMA) model used MINITAB 16.0 and Microsof Excel that has been developed then applied by 3 respondents. Based on the results of the study, more detailed stages of the arima model and n 3 respondents both got a correlation value of 0.96 for Nino SST 3.4 original value and model value, correlation 0.92 for 1 year validation and correlation 0.99 ENSO prediction for 1 year (12 months) ahead. Thus the development of the ARIMA model stage is very effective to be used to predict climate such as ENSO events and other ocean climate phenomena.