Implementasi Sistem Prediksi Saham Real-Time dengan Integrasi Yahoo Finance API dan Machine Learning di Google Colab - Muhammmad Faiq Abdi; Yonhendri (Intitut Agama Islam Nasional Laa Roiba Bogor, 2025)
The issue of stock price prediction is a critical topic in the financial world, where accurate predictions are essential for making better investment decisions. This research develops a real-time stock price prediction system by integrating the Yahoo Finance API and machine learning algorithms, executed on the Google Colab platform. This system allows for direct retrieval of stock market data from Yahoo Finance to analyze data patterns and generate more accurate stock price predictions. The methods used include collecting historical and real-time data from the Yahoo Finance API, data preprocessing, training models using Long Short Term Memory (LSTM), validating the model with K-Fold Cross Validation, and evaluating performance using various standard metrics. The development and implementation of the model are carried out on Google Colab. The results show that the LSTM model can provide high-accuracy stock price predictions. This system significantly contributes to improving stock price prediction accuracy and helps investors make better decisions based on real-time data