Prediksi Harga Emas dengan Menggunakan Algoritma Support Vector Regression (Svr) dan Linear Regression (LR)
Abstract
Gold is a precious metal that is in great demand, because generally the value of gold tends to be stable and the price per gram will increase every year. Gold investment is divided into two, there are digital investments and physical investments. Sometimes in this gold investment investors will experience losses as well as gain profits. To minimize this, a technique is needed to predict the price of gold. Prediction technique is one of the techniques used in Machine Learning. This study aims to predict the price of gold using the Support Vector Regression (SVR) and Linear Regression (LR) algorithms as a comparison. The software that will be used is Jupyter Notebook using the Python programming language. The final result obtained is a graph of the gold price and of the MSE (Mean Squad Error) error on the the SVR Algorithm is 7.524505784357 and LR Algorithm is 4.04444791059
References
Nugroho Dwi, S. (2015). Penerapan Algoritma Support Vector Machine untuk Prediksi Harga Emas. Informatika UPGRIS, 1(1), 10-19.
Azzahra, M., Setiawan, B. D., & Adikara, P. P. (2017). Optimasi Parameter Support Vector Regression Dengan Algoritme Genetika Untuk Prediksi Harga Emas. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer e-ISSN, 2548, 964X.
Priyadi, I., Santony, J., & Na'am, J. (2019). Data mining predictive modeling for prediction of gold prices based on dollar exchange rates, BI rates and world crude oil prices. Indonesian Journal of Artificial Intelligence and Data Mining, 2(2), 93-100.
Riyanto, V., Hamid, A., & Ridwansyah, R. (2019). Prediction of Student Graduation Time Using the Best Algorithm. Indonesian Journal of Artificial Intelligence and Data Mining, 2(1), 1-9.
Mubarok, A. PENERAPAN ALGORITMA SUPPORT VECTOR REGRESSION (SVR) DALAM PREDIKSI SAHAM EMAS (ANTM. JK).
Bode, A. (2019). Perbandingan Metode Prediksi Support Vector Machine Dan Linear Regression Menggunakan Backward Elimination Pada Produksi Minyak Kelapa. Simtek: jurnal sistem informasi dan teknik komputer, 4(2), 104-107.
Alfredo, A., Jondri, J., & Rismala, R. (2015). Prediksi Harga Saham menggunakan Support Vector Regression dan Firefly Algorithm. eProceedings of Engineering, 2(2).
Masruroh, M. (2020). Perbandingan Metode Regresi Linear Dan Neural Network Backpropagation Dalam Prediksi Nilai Ujian Nasional Siswa Smp Menggunakan Software R. Joutica, 5(1), 331-336.
Yasin, H., Prahutama, A., & Utami, T. W. (2014). Prediksi harga saham menggunakan support vector regression dengan algoritma grid search. Media Statistika, 7(1), 29-35.
Laksana, T. G. (2013). Perbandingan Algoritma Neural Network (NN) dan Support Vector Machines (SVM) dalam Peramalan Penduduk Miskin di Indonesia. Inf. Comput. Technol, 1(1), 49-58.
