Article Per Year (5 Year)
p-Index From 2021 - 2026
2.668
P-Index
This Author published in this journals
All Journal KADIKMA Jurnal Mirai Management JURNAL PENDIDIKAN DASAR PERKHASA YUME : Journal of Management Jurnal Investasi J-PiMat : Jurnal Pendidikan Matematika Jurnal Pengabdian Masyarakat Khatulistiwa Journal of Applied Data Sciences ALEXANDRIA: Journal of Economics, Business, and Entrepreneurship Jurnal Minfo Polgan (JMP) Journal of Computer Science and Information Systems (JCoInS) Social Sciences Insights Journal
Anita Sri Rejeki Hutagaol, Anita Sri Rejeki
Unknown Affiliation
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 20 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Computer Science and Information Systems (JCoInS)

 1 
Rekayasa Fitur dan Gradient Boosting untuk Prediksi Harga Saham Pada Pasar Saham Indonesia Rambe, Bhakti Helvi; Munthe, Ibnu Rasyid; Hanum, Fauziah; Hutagaol, Anita Sri Rejeki
Journal of Computer Science and Information System(JCoInS) Vol 7, No 1: JCoInS | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i1.8945

Abstract

This study aims to analyze the comparative performance of three machine learning models Neural Network, Random Forest, and XGBoost in predicting the stock price of Bank Rakyat Indonesia (BBRI.JK) based on feature engineering integration. The background of this study is based on the need to develop accurate and efficient predictive models to deal with stock market volatility. The Data used covers the period 2010-2025 with the application of technical indicators such as Moving Average (MA), Relative Strength Index (RSI), volatility, and price momentum as the main features. The research method uses a machine learning approach based on supervised learning with a five-fold cross validation process. Model evaluation was conducted using quantitative metrics including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), coefficient of determination (R2), and Mean Absolute Percentage Error (MAPE). The results showed that XGBoost produced the Best Performance With R2 = 0.9451, MAE = 87.3129,and MSE = 10327.1187, followed by Random Forest (R2 = 0.9233) and Neural Network (R2 = 0.9120). The XGBoost Model proved to be the most stable and efficient in handling nonlinear data as well as extreme price fluctuations. The discussion confirms that the integration of engineering features improves the generalization capability of the model and lowers the prediction error rate significantly. Future research is recommended to include macroeconomic variables, sentiment data, and reinforcement learning approaches to broaden the scope and improve the model's adaptability to global financial market dynamics.
Co-Authors Ade Parlaungan Nasution, Ade Parlaungan Ali Djamhuri Amanda, Ade Trya Anggie Yolanda Ritonga Becham, David Dwi Cahyadi Wibowo, Dwi Cahyadi Gulo, Nur Ainun Hanum, Fauziah Hasibuan, Muhammad Ridho Rahmansyah Hermawati, Dewi Limbong, Christine Herawati Lubis, Junita Lubis, Rizka Putri Permata Melinda Rismawati, Melinda Mizardi, Alvro Munthe, Ibnu Rasyid Nurhayana, Inung Oktaviani, Devia Salisa Olenggius Jiran Dores, Olenggius Jiran Dores Pranando, R Andy Pristiyono, Pristiyono Raden Mohamad Herdian Bhakti Rambe, Bhakti Helvi Richi Andrianto Ritonga, Anggie Yolanda Safri, Hayanuddin Samosir, Syahnita Sari, Devi Khalima Simanjorang, Elida Florentina Sinaga Sinaga Simanjorang, Elida Florentina Sitanggang, Kamsia Dorliana Sopia, Nurapni Subakti, Dedi Syahputra, Rizki Tarigan, Armansyah Winata, Winata Yudi Prayoga Zulkarnain Nasution Zulkifli Musannip Efendi Siregar