PERAMALAN HARGA SAHAM PT INDOFOOD SUKSES MAKMUR TBK MENGGUNAKAN MODEL HIBRIDA SINGULAR SPECTRUM ANALYSIS (SSA) – AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

Abstract

Daily stock price data can be predicted by examining the data pattern. SSA is a flexible nonparametric forecasting technique. ARIMA is a good technique for basic forecasting. In order to increase accuracy, hybrid method combines two or more forecasting techniques. The purpose of this study is to use the SSA-ARIMA hybrid model to forecast the stock price of PT Indofood Sukses Makmur. The August through December 2023 daily closing stock price data of PT Indofood Sukses Makmur Tbk is the source of the data. Testing data begins on November 29^th and ends on December 29^th, 2023, while training data runs from August 1^st to November 28^th 2023. SSA is used to model the training data. ARIMA is used to simulate the SSA residuals. Summing the outcomes of SSA and ARIMA forecasting yields the forecast for the SSA-ARIMA hybrid model. The findings demonstrated that the MAPE values of the SSA-ARIMA(1,0,0) and SSA-ARIMA(0,0,1) models were 1.54% for testing data and 0.82% for training data. Therefore, the SSA-ARIMA hybrid model has very good forecasting ability for PT Indofood Sukses Makmur's stock price.