Implementasi Algoritma Neural Network Dengan Optimisasi Hyperparameter Untuk Prediksi Harga Saham

Muhammad Rizky Pribadi
Evi Maria (Universitas Kristen Satya Wacana)
Suryasatria Trihadaru (Universitas Kristen Satya Wacana)
Sri Yulianto Joko Prasetyo (Universitas Kristen Satya Wacana)
Sutarto Wijono (Universitas Kristen Satya Wacana)

JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Vol 9 No 4 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)

Stocks are one of the investment instruments that are currently in demand because they have a greater return value than saving in a bank. It's just that investing in stocks has the risk of decreasing the value of the stock price, which can make investors lose money. Mining stocks are currently the prima donna of investors, because their value continues to rise. However, buying shares at the right time is still an obstacle, therefore a stock price prediction is needed that can help investors determine the right time to buy mining shares. The use of machine learning can be done to predict stock prices. The data used in this research is PTBA stock price data from 2017 – 2022. In this study, the Neural Network algorithm is used with hyperparameter optimization. In this study, the RMSE value was 30.634. A small RMSE value indicates that the Neural Network algorithm can be used to predict PTBA's stock price.