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

Edra Arkananta Gultom; Kartika Dewi Sri Susilowati; Anik Kusmintarti

doi:10.55927/fjst.v3i11.12216

Authors

Edra Arkananta Gultom State Polytechnic of Malang
Kartika Dewi Sri Susilowati State Polytechnic of Malang
Anik Kusmintarti State Polytechnic of Malang

DOI:

https://doi.org/10.55927/fjst.v3i11.12216

Keywords:

Stock Forecasting, Dashboard Design, Artificial Intelligence, Machine Learning

Abstract

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.

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