Syaifulloh, Dafauzan Bilal (2026) Prediksi Indeks Saham Harga Penutupan PT Jamu dan Farmasi Sido Muncul Tbk Menggunakan Hybrid Model CEEMDAN-ARIMA-LSTM. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
The movement of stock prices exhibits non-linear and non-stationary characteristics, making it difficult to predict using a single method. This study proposes a hybrid CEEMDAN–ARIMA–LSTM model to forecast the closing stock price of PT Industri Jamu dan Farmasi Sido Muncul Tbk (SIDO) using historical data from 2020 to 2025. The data were decomposed using CEEMDAN into several Intrinsic Mode Functions (IMFs), and the complexity of each IMF was analyzed using Sample Entropy (SampEn). IMFs with linear patterns were predicted using ARIMA, while those with non-linear patterns were modeled using LSTM. All component predictions were then reconstructed to form the final forecasting output.Evaluation using MAPE, RMSE, and MAE shows that the hybrid CEEMDAN–ARIMA–LSTM model provides better predictive accuracy compared to single models, as it captures both linear and non-linear components simultaneously. This approach proves to be effective in improving the forecasting performance for SIDO stock prices and offers a promising alternative for complex financial time series prediction. Keywords: Stock Prediction, CEEMDAN, ARIMA, LSTM, Sample Entropy, Time Series, Hybrid Model.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76.6 Computer Programming |
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| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | dafauzan dafa bilal syaifulloh | ||||||||||||
| Date Deposited: | 19 Jan 2026 09:01 | ||||||||||||
| Last Modified: | 20 Jan 2026 01:39 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/48871 |
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