LQ45 Stock Index Prediction using k-Nearest Neighbors Regression
Open accessAbstract
The capital market is an organized financial system consisting of commercial banks, intermediary institutions in the financial sector and all outstanding securities. One of the benefits of the capital market is creating opportunities for the community to participate in economic activities, especially in investing. In daily stock trading activities, stock prices tend to have fluctuated. Therefore, stock price prediction is needed to help investors make decisions when they want to buy or sell their shares. One asset for investment is shares. One of the stock price indices that attracts many investors is the LQ45 stock index on the Indonesian stock exchange. One of the algorithms that can be used to predict is the k-Nearest Neighbors (kNN) algorithm. In the previous study, kNN had a higher accuracy than the moving average method of 14.7%. This study uses kNN regression method because it predicts numerical data. The results of the research in making the LQ45 stock index prediction application have been successfully built. The highest accuracy achieved reaches 91.81% by WSKT share.
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- Authors
- Informatics Department, U. M. N., Tanuwijaya*, J., Hansun, S., & Informatics Department, U. M. N.
- ORCID
- Hansun, Seng
- Venue
- International Journal of Recent Technology and Engineering (IJRTE)
- Publisher
- Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
- Published
- 2019-09-30
- Volume
- 8
- Issue
- 3
- Pages
- 2388-2391
- ISSN
- 2277-3878 (ISSN-L)
- OpenAlex
- W4248439738
- Cited by
- 29
- References
- 0
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 10 · 2023: 4 · 2022: 7 · 2021: 2 · 2020: 1
- Type
- conference abstract
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- International Journal of Recent Technology and Engineering (IJRTE) (publishedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- stock price prediction, k-nearest neighbors regression, Indonesia Stock Exchange, capital markets, investment decision support
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