Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)
Need for future price forecasts by investors faces difficulties in achieving accurate predictions because market changes exist. Standard single models do not accurately model stock market behaviors because of their complex nature. The problem solution implemented by the study involves combining K-Ne...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2025
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2177/ http://eprints.intimal.edu.my/2177/1/ij2025_28.pdf http://eprints.intimal.edu.my/2177/2/726 |
| _version_ | 1848766985348841472 |
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| author | Muhammad, Tamami Sefto, Pratama Zaenuddin, . Haldi, Budiman Erfan, Karyadiputra Desy Ika, Puspitasari |
| author_facet | Muhammad, Tamami Sefto, Pratama Zaenuddin, . Haldi, Budiman Erfan, Karyadiputra Desy Ika, Puspitasari |
| author_sort | Muhammad, Tamami |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Need for future price forecasts by investors faces difficulties in achieving accurate predictions because market changes exist. Standard single models do not accurately model stock market behaviors because of their complex nature. The problem solution implemented by the study involves combining K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) to create ensemble stacking. Research personnel collected Bank Rakyat Indonesia's (BRI) historical stock price data using KNN and SVM models. Studio performance delivers superior predictive results with lower error rates than KNN and SVM models that operate individually. Study results demonstrate stacking technology produces the most desirable results for stock market price prediction. |
| first_indexed | 2025-11-14T11:59:50Z |
| format | Article |
| id | intimal-2177 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:59:50Z |
| publishDate | 2025 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-21772025-09-20T07:07:05Z http://eprints.intimal.edu.my/2177/ Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) Muhammad, Tamami Sefto, Pratama Zaenuddin, . Haldi, Budiman Erfan, Karyadiputra Desy Ika, Puspitasari HG Finance QA76 Computer software T Technology (General) Need for future price forecasts by investors faces difficulties in achieving accurate predictions because market changes exist. Standard single models do not accurately model stock market behaviors because of their complex nature. The problem solution implemented by the study involves combining K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) to create ensemble stacking. Research personnel collected Bank Rakyat Indonesia's (BRI) historical stock price data using KNN and SVM models. Studio performance delivers superior predictive results with lower error rates than KNN and SVM models that operate individually. Study results demonstrate stacking technology produces the most desirable results for stock market price prediction. INTI International University 2025-09 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2177/1/ij2025_28.pdf text en cc_by_4 http://eprints.intimal.edu.my/2177/2/726 Muhammad, Tamami and Sefto, Pratama and Zaenuddin, . and Haldi, Budiman and Erfan, Karyadiputra and Desy Ika, Puspitasari (2025) Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM). INTI JOURNAL, 2025 (28). pp. 1-5. ISSN e2600-7320 https://intijournal.intimal.edu.my |
| spellingShingle | HG Finance QA76 Computer software T Technology (General) Muhammad, Tamami Sefto, Pratama Zaenuddin, . Haldi, Budiman Erfan, Karyadiputra Desy Ika, Puspitasari Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title | Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title_full | Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title_fullStr | Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title_full_unstemmed | Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title_short | Stock Price Prediction of Bank Rakyat Indonesia Using an Ensemble Stacking Model of K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) |
| title_sort | stock price prediction of bank rakyat indonesia using an ensemble stacking model of k-nearest neighbors (knn) and support vector machine (svm) |
| topic | HG Finance QA76 Computer software T Technology (General) |
| url | http://eprints.intimal.edu.my/2177/ http://eprints.intimal.edu.my/2177/ http://eprints.intimal.edu.my/2177/1/ij2025_28.pdf http://eprints.intimal.edu.my/2177/2/726 |