Prediksi Harga Saham Menggunakan Pendekatan Machine Learning Dan Deep Learnin…

High stock price volatility in Indonesia's infrastructure and energy sectors poses challenges in predicting price movements. This study aims to implement and compare the accuracy of K-Nearest Neighbors (KNN) machine learning model and Long Short-Term Memory (LSTM) deep learning model in predicting stock prices in these sectors. The research stages include data preprocessing, model training, eva…