Studi Literatur Mengenai Prediksi Harga Saham Menggunakan Machine Learning
DOI:
https://doi.org/10.33005/santika.v1i0.20Keywords:
Prediksi Harga Saham, Machine Learning, Regresi, Jaringan Syaraf Tiruan, Studi LiteraturAbstract
Prediksi harga saham tidak hanya menarik bagi para ekonom namun juga menarik dibahas untuk para analis. Harga saham yang berfluktuasi dan terpengaruhi oleh banyak faktor menyebabkan prediksi dengan berbagai macam teknik dilakukan. Salah satu metode yang dapat memprediksi harga saham adalah dengan Machine Learning. Pada penelitian ini membahas mengenai studi literatur variabel masukan, metode, dan hasil dari literature terdahulu. Harga pembukaan, penutupan, terendah, dan tertinggi saham harian merupakan variabel masukan yang paling banyak digunakan. Metode yang paling banyak digunakan adalah jaringan syaraf tiruan. Metode tersebut juga menghasilkan tingkat kesalahan yang relatif kecil.
References
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[2] D. Arista and Astohar, “ANALISIS FAKTOR – FAKTOR YANG MEMPENGARUHI RETURN SAHAM (Kasus pada Perusahaan Manufaktur yang Go Public di BEI periode tahun 2005 - 2009),” J. Ilmu Manaj. dan Akunt. Terap., vol. 14, no. 1, p. 29, 2013.
[3] E. Mala, S. Rochman, A. Djunaidy, T. Informatika, and F. T. Informasi, “Prediksi harga saham yang mempertimbangkan faktor eksternal menggunakan jaringan saraf tiruan,” vol. 1, no. 2, pp. 5–11, 2014.
[4] L. E. Siahaan, R. F. Umbara, S. Si, and Y. Sibaroni, “Prediksi Indeks Harga Saham dengan Metode Gabungan Support Vector Regression dan Jaringan,” vol. 2, pp. 21–30, 2017.
[5] A. Novita, “Prediksi Pergerakan Harga Saham Pada Bank Terbesar Di Indonesia Dengan Metode Backpropagation Neural Network,” pp. 965–972, 2013.
[6] A. Izzah and R. Widyastuti, “Prediksi Harga Saham Menggunakan Improved Multiple Linear Regression Untuk Pencegahan Data Outlier,” vol. 2, no. 3, pp. 141–149, 2017.
[7] L. Y. Kurniawati, H. Tjandrasa, and I. Arieshanti, “Prediksi pergerakan harga saham menggunakan support vector regression,” J. SimanteC, vol. VIII, no. 1, pp. 11–21, 2013.
[8] Z. Rustam and P. Kintandani, “Application of Support Vector Regression in Indonesian Stock Price Prediction with Feature Selection Using Particle Swarm Optimisation,” Model. Simul. Eng., vol. 2019, 2019.
[9] M. Z. Asghar, F. Rahman, F. M. Kundi, and S. Ahmad, Development of stock market trend prediction system using multiple regression, vol. 25, no. 3. Springer US, 2019.
[10] S. Mohan, S. Mullapudi, S. Sammeta, P. Vijayvergia, and D. C. Anastasiu, “Stock price prediction using news sentiment analysis,” Proc. - 5th IEEE Int. Conf. Big Data Serv. Appl. BigDataService 2019, Work. Big Data Water Resour. Environ. Hydraul. Eng. Work. Medical, Heal. Using Big Data Technol., pp. 205–208, 2019.
[11] I. R. Parray, S. S. Khurana, M. Kumar, and A. A. Altalbe, “Time series data analysis of stock price movement using machine learning techniques,” Soft Comput., vol. 0123456789, 2020.
[12] T. Cakra, “Stock Price Prediction using Linear Regression based on Sentiment Analysis,” Int. J. Sci. Eng. Res., vol. 6, no. 3, pp. 1655–1659, 2015.
[13] H. L. Siew and M. J. Nordin, “Regression techniques for the prediction of stock price trend,” ICSSBE 2012 - Proceedings, 2012 Int. Conf. Stat. Sci. Bus. Eng. "Empowering Decis. Mak. with Stat. Sci., pp. 99–103, 2012.
[14] L. Zhao and L. Wang, “Price Trend Prediction of Stock Market Using Outlier Data Mining Algorithm,” Proc. - 2015 IEEE 5th Int. Conf. Big Data Cloud Comput. BDCloud 2015, pp. 93–98, 2015.
[15] Y. Wang and Y. Wang, “Using social media mining technology to assist in price prediction of stock market,” Proc. 2016 IEEE Int. Conf. Big Data Anal. ICBDA 2016, 2016.
[16] W. Khan, M. A. Ghazanfar, M. A. Azam, A. Karami, K. H. Alyoubi, and A. S. Alfakeeh, “Stock market prediction using machine learning classifiers and social media, news,” J. Ambient Intell. Humaniz. Comput., no. 0123456789, 2020.
[17] D. J. Olive, Linear regression. 2017.
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Published
2020-11-01
How to Cite
Hindrayani, K. M., Mas Diyasa, I. G. S., Riyantoko, P. A., & Fahrudin, T. M. (2020). Studi Literatur Mengenai Prediksi Harga Saham Menggunakan Machine Learning. Prosiding Seminar Nasional Informatika Bela Negara, 1, 71–75. https://doi.org/10.33005/santika.v1i0.20
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