Analisis Autoregressive Integrated Moving Average (ARIMA) dengan Intervensi Double Input pada Prediksi Harga Saham

Gita Arinda Maulidya, Neva Satyahadewi, Nur'ainul Miftahul Huda

Abstract

Intervention analysis is the time series analysis used in a time series model that experiences an intervention event. Intervention is an event that can cause time series data to change patterns caused by external or internal factors such as changes in government policy, advertising promotions, environmental regulations, and others. This research uses the ARIMA analysis method of double input step function intervention with daily data on the closing share prices of PT Adaro Energy Indonesia for the period 7 March 2022 to 7 March 2023 because in that period there are two points that are thought to be interventions that have an impact on changes in the ADRO’s share prices over a long period of time. The aim of this research is to analyze the intervention ARIMA model and predict the closing price of PT Adaro Energy Indonesia for the next five-days period. The ARIMA analysis steps are based on the ARIMA model through the process of stationarity data (variance and mean), order identification, parameter estimation, and diagnostic examination. The best ARIMA model used to predict ADRO's closing share price is the ARIMA (2,1,2) model, which is obtained based on the smallest AIC, MAPE, and RMSE values. The prediction results in this research show that the predictions produced for the next five-days period are classified as very good because they have a MAPE value on training data of 1,96% and a MAPE value on testing data of 1,74%.


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DOI: https://doi.org/10.13057/ijas.v7i1.85229

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