<![CDATA[This study explores the role of intelligent algorithms in assessing the financial feasibility of start-up entrepreneurs in Indonesia, employing a qualitative approach with insights from five key informants. Traditional financial assessment methods are found to be limited by factors such as market volatility, lack of historical data, and resource constraints. Intelligent algorithms offer transformative potential, with advantages in predictive accuracy, scenario simulations, and efficiency. However, barriers including technical expertise, cost constraints, and data availability hinder their adoption. A hybrid framework integrating qualitative insights and algorithmic tools is proposed to address these challenges and enhance decision-making for start-ups. The findings provide a practical roadmap for leveraging advanced technologies in the dynamic and diverse Indonesian start-up ecosystem.]]>
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