Design of a Stock Forecasting Dashboard using Python-Streamlit and FB Prophet with AI

Gultom, Edra Arkananta
Susilowati, Kartika Dewi Sri
Kusmintarti, Anik

Formosa Journal of Science and Technology (FJST)
Vol. 3 No. 11 (2024): November 2024

This research aims to develop a stock price forecasting application using time series analysis with the Prophet model. The application retrieves historical stock data from Yahoo Finance (2015–present) for Indonesian stocks, which is then processed and analyzed to predict future prices. The study integrates yfinance for data collection, Prophet for forecasting, and Plotly for visualizing the results. The application allows users to select stocks and customize prediction periods (1–4 years). The findings indicate that while the model provides useful short-term predictions, its accuracy is limited by market volatility and external factors. This tool can support decision-making but should be used in conjunction with other forecasting methods.