Penerapan Gradient Boosting Regression dalam Prediksi Pergerakan Harga Emas Berdasarkan Pendekatan Moving Average of VWAP
DOI:
https://doi.org/10.22441/incomtech.v15i1.28304Kata Kunci:
Emas, Gradient Boosting Regeression, Moving Average, VWAP.Abstrak
Pergerakan Harga emas dipengaruhi oleh berbagai faktor ekonomi, inflasi, penawaran dan permintaan, serta kebijakan moneter, yang membuat prediksi Harga emas menjadi penting bagi investor. Penelitian ini bertujuan untuk mengembangkan model prediksi Harga emas menggunakan pendekatan Moving Average of VWAP dan Algoritma Gradient Boosting Regression. Data diambil dari situs www.investing.com, mencakup periode 14 Januari 2016 hingga 12 April 2024. Metode penelitian meliputi pembersihan data. Penskalaan dengan StandardScaler, dan pembagian data menjadi set pelatihan dan pengujian, Moving Average of VWAP digunakan untuk menganalisis Harga berdasarkan volume perdagangan, sementara Algoritma Gradient Boosting Regression digunakan untuk klasifikasi dan prediksi Harga actual dan prediksi. Hasil penelitian menunjukan Tingkat akurasi yang sangat tinggi dengan R-Squared (R2) mencapai 0.99 dan evaluasi kinerja model menunjukan MAE sebesar 6.2955, MSE sebesar 78.0802, RMSE sebesar 8.8317. hasil ini menunjukan bahwa model prediksi yang dihasilkan dapat menjadi alat yang efektif bagi investor dalam pengambilan Keputusan investasi emas yang lebih informasional dan strategis.
Unduhan
Referensi
Z. H. Kilimci, “Ensemble Regression-Based Gold Price ( XAU / USD ) Prediction,” vol. 2, no. June, pp. 7–12, 2022.
Z. Alameer, M. A. Elaziz, A. A. Ewees, H. Ye, and Z. Jianhua, “Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm,” Resour. Policy, 2019, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0301420718304926
G. Smith, “Data mining fool’s gold,” 2020, doi: 10.1177/0268396220915600.
H. Y. Wu, S. W. Lei, and J. L. Ha, “Analyzing Market Trends Using a Visual Approach,” … J. Econ. Manag. Syst., 2022, [Online]. Available: https://www.iaras.org/iaras/home/caijems/analyzing-market-trends-using-a-visual-approach
H. N. Gudavalli and K. V. R. Kancherla, Predicting Cryptocurrency Prices with Machine Learning Algorithms: A Comparative Analysis. diva-portal.org, 2023. [Online]. Available: https://www.diva-portal.org/smash/record.jsf?pid=diva2:1778251
P. Simamora, S. A. Pasaribu, and V. Wijaya, “Peningkatan dan Optimalisasi Prediksi Harga Emas Menggunakan Metode Combine Machine Learning Random Forest dan Gradient Boosting,” vol. 01, pp. 42–51, 2024.
Y. Chithra, P. Kiran, and P. B. Manoj, “The Novel Method for Data Preprocessing CLI,” pp. 117–120, 2023.
L. Zhang, T. Wu, S. Lahrichi, and ..., “A data science pipeline for algorithmic trading: A comparative study of applications for finance and cryptoeconomics,” 2022 IEEE …, 2022, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9881799/
S. Alam, F. S. Al-ismail, and S. Hossain, “Ensemble Machine-Learning Models for Accurate Prediction of Solar Irradiation in Bangladesh,” pp. 1–15, 2023.
W. F. Mustafa, S. Hidayat, and D. H. Fudholi, “Prediksi Retensi Pengguna Baru Shopee Menggunakan Machine Learning,” vol. 8, pp. 612–623, 2024, doi: 10.30865/mib.v8i1.7074.
R. A. V. and K. N. L. Craig A. Mertler, Advanced and Multivariate Statistical Methods.
Trivusi, “Perbedaan MAE, MSE, RMSE, dan MAPE pada Data Science,” 2023. https://www.trivusi.web.id/2023/03/perbedaan-mae-mse-rmse-dan-mape.html
M. Pauzan, “Rancang Bangun Sistem Kontrol Watermeter PDAM Berbasis IoT,” vol. 14, no. 3, pp. 242–257, 2022.
W. Rizka, U. Fadilah, D. Agfiannisa, and Y. Azhar, “Analisis Prediksi Harga Saham PT . Telekomunikasi Indonesia Menggunakan Metode Support Vector Machine,” vol. 5, no. 2, 2020.
D. Chicco, M. J. Warrens, and G. Jurman, “The coef fi cient of determination R-squared is more informative than SMAPE , MAE , MAPE , MSE and RMSE in regression analysis evaluation,” pp. 1–24, 2021, doi: 10.7717/peerj-cs.623.
A. Purwanto and Y. Sudargini, “Partial Least Squares Structural Squation Modeling ( PLS-SEM ) Analysis for Social and Management Research : A Literature Review Journal of Industrial Engineering & Management Research,” vol. 2, no. 4, pp. 114–123.
Unduhan
File Tambahan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
The copyright to this article is transferred to Universitas Mercu Buana (UMB) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to UMB. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment.
We declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.
Furthermore, I/We hereby transfer the unlimited rights of publication of the above mentioned paper in whole to UMB. The copyright transfer covers the exclusive right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Retained Rights/Terms and Conditions
1. Authors retain all proprietary rights in any process, procedure, or article of manufacture described in the Work.
2. Authors may reproduce or authorize others to reproduce the Work or derivative works for the authors personal use or for company use, provided that the source and the UMB copyright notice are indicated, the copies are not used in any way that implies UMB endorsement of a product or service of any employer, and the copies themselves are not offered for sale.
3. Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
