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http://repository.ipb.ac.id/handle/123456789/163496| Title: | Perbandingan Kinerja Model FTS-Markov Chain dan Geometric Brownian Motion dalam Memprediksi Harga Saham BBRI |
| Other Titles: | |
| Authors: | Mangku, I Wayan Purnaba, I Gusti Putu Aulia, Syifa |
| Issue Date: | 2025 |
| Publisher: | IPB University |
| Abstract: | Saham merupakan instrumen investasi yang paling diminati oleh investor di pasar modal. Harga saham bersifat fluktuatif sehingga terjadi peningkatan dan penurunan harga. Model stokastik yang dapat digunakan untuk memprediksi harga saham yaitu Fuzzy Time Series Markov Chain (FTS-Markov Chain) dan Geometric Brownian Motion (GBM). Penelitian ini bertujuan membandingkan kinerja dari model FTS-Markov Chain dan GBM dalam memprediksi harga saham. Evaluasi kinerja model dilakukan dengan membandingkan nilai Mean Absolute Percentage Error (MAPE) dari kedua model prediksi. Data yang digunakan yaitu data harian harga penutupan saham BBRI sejak 01 November 2023 hingga 31 Oktober 2024. Hasil penelitian menunjukkan model FTS-Markov Chain menghasilkan nilai MAPE yang lebih kecil dibandingkan model GBM, model FTS-Markov Chain memiliki pola prediksi yang cenderung sama dengan data aktual dan mampu mengidentifikasi fluktuasi harga saham. Oleh sebab itu, model FTS-Markov Chain memiliki kinerja yang lebih baik dalam memprediksi harga saham BBRI. Stocks are the most popular investment instruments among investors in the capital market. Stock prices are fluctuating, leading to price increases and decreases. Stochastic models that can be used to predict stock prices include the Fuzzy Time Series Markov Chain (FTS-Markov Chain) and Geometric Brownian Motion (GBM). This study aims to compare the performance of the FTS-Markov Chain and GBM models in predicting stock prices. Model performance evaluation was conducted by comparing the Mean Absolute Percentage Error (MAPE) values of both prediction models. The data used consists of daily closing stock prices of BBRI from November 1, 2023, to October 31, 2024. The results indicate that the FTS-Markov Chain model produces a lower MAPE value than the GBM model. The FTS-Markov Chain model exhibits a prediction pattern that closely aligns with actual data and effectively identifies stock price fluctuations. Therefore, the FTS-Markov Chain model demonstrates superior performance in predicting BBRI stock prices. |
| URI: | http://repository.ipb.ac.id/handle/123456789/163496 |
| Appears in Collections: | UT - Mathematics |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| cover_G5401211036_7a3962526966437d84b48ba568290560.pdf | Cover | 502.04 kB | Adobe PDF | View/Open |
| fulltext_G5401211036_c0cd7526815649969ca4575a52a2d10e.pdf Restricted Access | Fulltext | 827.66 kB | Adobe PDF | View/Open |
| lampiran_G5401211036_9706b6521a6f4e24bfb021e1ecfca288.pdf Restricted Access | Lampiran | 393.92 kB | Adobe PDF | View/Open |
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