Primandari, Arum Handini and Iskandar, Shafa Amalia (2024) A Multivariate Approach: Forecasting Jakarta Composite Using Prophet Facebook. Jurnal Statistika dan Aplikasinya, 8 (1). pp. 128-137. ISSN 2620-8369
Full text not available from this repository.Abstract
The Jakarta Composite Index (JCI, Composite Stock Price Index / IHSG) presents the average share price movement of companies listed on the Indonesia Stock Exchange (BEI/IDX), which can reflect the stock market performance. JCI forecasting can provide benefits for investors regarding risk management. On the other hand, gold is a low-risk asset with no credit risk and maintains its value over time. During the pandemic, gold prices increased significantly while stock prices decreased sharply, so gold prices can be used as a regressor in forecasting the JCI. Researchers obtained historical data on the JCI and gold prices (dollars/ounce) from January 1, 2018, to December 31, 2022. The approach used in this research is multivariate in the Prophet model. The Prophet model uses a procedure to estimate time series data based on an additive model with trends that can be adjusted for annual, weekly, and daily seasonality. Based on the analysis results, the Prophet's multivariate approach is the best method for predicting the JCI compared to the univariate approach. The parameters used in the model are as follows: yearly seasonality, multiplicative seasonality mode, seasonality prior scale, namely 0.5, and changepoint prior scale, namely 0.001. The Mean Absolute Percentage Error (MAPE) obtained from the model is 2.78%.
| Item Type: | Article |
|---|---|
| Subjects: | Sains > Matematika |
| Depositing User: | OJS LPPM UNJ . |
| Date Deposited: | 09 Mar 2025 03:53 |
| Last Modified: | 09 Mar 2025 03:53 |
| URI: | http://repository.unj.ac.id/id/eprint/55298 |
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