Heriyanto Heriyant

Papers

Total Citations

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About

Heriyanto Heriyant is an emerging researcher in computational finance and data-driven decision systems, with a focus on integrating machine learning into accessible trading tools. His most cited work, “Trading Simulation Using Python and Visualization on Streamlit with Machine Learning Decision Tree” (2022, 5 citations), addresses a critical gap in retail investing: the proliferation of fraudulent trading schemes. By developing a transparent simulation platform that combines Python, Streamlit, and decision tree algorithms, Heriyant empowers novice investors to test strategies without falling prey to illegal robots. This contribution not only demystifies algorithmic trading but also promotes financial literacy in a volatile market. His research underscores the importance of ethical, user-friendly technology in democratizing investment knowledge. While his citation count is still growing, Heriyant’s work resonates with practitioners seeking practical, low-risk entry points into machine learning for finance. As fraudulent investment schemes persist, his approach offers a replicable framework for safe, educational trading simulations—a timely and socially relevant achievement for students and researchers exploring the intersection of AI and personal finance.