SIANIPAR, JULIAN GABRIEL and Utami, Alvi Syahrini (2025) KLASIFIKASI ARAH PERGERAKAN INDEKS HARGA SAHAM GABUNGAN DI BURSA EFEK INDONESIA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM). Undergraduate thesis, Sriwijaya University.
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Abstract
The Indonesian stock market as a strategic investment instrument with high volatility requires an accurate prediction system to minimize investor losses and increase profits. The technical and fundamental analysis methods that have been used have limitations, such as reliance on historical data and lack of consideration for external factors. With technological advancements, machine learning algorithms such as Support Vector Machine (SVM) have become an option to improve prediction accuracy. Therefore, a classification model for the movement direction of the Composite Stock Price Index (IHSG) on the Indonesia Stock Exchange will be developed using the SVM algorithm, which is chosen to overcome the limitations of the aforementioned technical and fundamental analysis methods in order to produce more optimal predictions. This research tests the best parameter combination from three parameters: C, γ, and number of iterations to produce the best model. From the results of the experiment, the best parameter combination was obtained with values of C = 0.1, γ = 1, and number of iterations = 200, resulting in a model with an accuracy of 91.79%. The results of this study show that SVM can be an effective tool in predicting the movement direction of IHSG
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Ilmu Komputer, Teknik Informatika |
| Subjects: | T Technology > T Technology (General) > T173.2-174.5 Technological change > T174 Technological forecasting T Technology > TA Engineering (General). Civil engineering (General) > TA174.A385 Engineering design--Data processing. Manufacturing processes--Data processing. Computer integrated manufacturing systems. Manufacturing processes--Automation. CAD/CAM systems. |
| Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
| Depositing User: | Julian Gabriel Sianipar |
| Date Deposited: | 22 Jul 2025 01:58 |
| Last Modified: | 22 Jul 2025 01:58 |
| URI: | http://repository.unsri.ac.id/id/eprint/179611 |
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