Imelda Uli Vistalina Simanjuntak

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About

Imelda Uli Vistalina Simanjuntak is a researcher at the intersection of financial technology, machine learning, and data visualization. Her work focuses on developing accessible tools for retail investors, particularly in the volatile realms of stock and cryptocurrency trading. Her most-cited paper, "Trading Simulation Using Python and Visualization on Streamlit with Machine Learning Decision Tree" (2022, 5 citations), addresses a critical problem: the proliferation of fraudulent trading robots that caused significant losses in early 2022. By combining Python-based simulation, interactive Streamlit dashboards, and decision tree algorithms, she created a transparent, educational framework that empowers users to test trading strategies without falling prey to scams. This contribution bridges the gap between complex quantitative finance and practical, user-friendly applications. Her research not only advances algorithmic trading education but also promotes financial literacy and risk awareness among non-experts. Simanjuntak’s work stands out for its direct societal impact—helping everyday investors make informed decisions in an era of digital financial uncertainty.