Sassung, Tety Octavia (2026) Prediksi Harga Saham PT Bank Central Asia Tbk (BBCA) dengan Penggabungan Metode Fuzzy Time Series Markov Chain dan Genetic Algorithm. Bachelor thesis, Institut Teknologi Kalimantan.
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Abstract
The capital market plays a vital role in supporting economic growth in Indonesia by serving as a bridge between investors and companies. The growing number of investors in Indonesia has led to an increased need for accurate stock price forecasts to guide investment decisions. One of the stocks with the largest market capitalization on the Indonesia Stock Exchange is PT Bank Central Asia Tbk (BBCA). Although BBCA is a blue-chip stock with strong fundamentals, its stock price continues to exhibit a volatile and complex pattern, necessitating a forecasting method capable of handling the uncertainty inherent in time-series data. This study aims to analyze the impact of using a Genetic Algorithm (GA) to optimize the formation of fuzzy intervals in the Fuzzy Time Series Markov Chain (FTS-MC) method. This study employs a quantitative approach using secondary data consisting of BBCA stock closing prices from January 2021 to December 2025, obtained from the investing.com website. The accuracy of the forecasting results was evaluated using the Mean Absolute Percentage Error (MAPE). The results show that the FTS-MC method produced a MAPE value of 1.261592675% for historical data and a MAPE value of 1.69621831% for the subsequent period, while the FTS-GA-MC method yielded a MAPE value of 1.471385811% for historical data and a MAPE value of 1.799498902% for the subsequent period. Thus, both can serve as alternatives for forecasting BBCA’s future stock price.
| Item Type: | Thesis (Bachelor) |
|---|---|
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Jurusan Matematika dan Teknologi Informasi > Matematika |
| Depositing User: | Tety Tety Octavia Sassung |
| Date Deposited: | 09 Jul 2026 02:07 |
| Last Modified: | 09 Jul 2026 02:07 |
| URI: | http://repository.itk.ac.id/id/eprint/26157 |
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