FORECASTING THE COMBINED STOCK PRICE INDEX (IHSG) USING THE RADIAL BASIS FUNCTION NEURAL NETWORK METHOD

Abstract

The capital market is one of the most critical factors in national economic development in Indonesia, as many industries and companies have previously used the capital market as a medium to absorb investment so that their financial position can be strengthened. The main indicator that can reflect the performance of the capital market is the Composite Stock Price Index (IHSG). The IHSG can be used to assess the general situation occurring in the market. Data IHSG is data obtained from the past and used to predict the future, also called time series data. Predictions on IHSG data need to be made so that investors can easily see capital market movements and know the policies that will be taken in the future. The Radial Basis Function Neural Network (RBFNN) method is used. RBFNN aims to get more efficient results because this method does not need to make the data stationary. The analysis results were carried out on a secondary data sample size of 1114 data, which obtained the highest forecasting price of Rp6157,619 on August 2, 2023. Meanwhile, the lowest forecast price on August 5, 2023, is IDR 5564,828 from August 1, 2023, to August 5, 2023.