STOCKSENTRA KOMPAS AI LITERASI INVESTASI SAHAM PEMULA

Abstrak

Indonesia has experienced rapid growth in young retail stock investors, yet investment literacy still lags
behind the pace of participation, increasing the risk of trend driven decisions. Novice investors are exposed
to fast moving digital information (news headlines and online discussions) and may accept “positive”
narratives without minimal analytical verification. This study designs and presents STOCKSENTRA
(Sentiment and Fundamental Tracker), an AI enabled educational prototype that integrates news
sentiment with issuer fundamentals to promote verificationoriented decision processes. Using a Design
Science Research (DSR) approach, the artifact combines (1) news based sentiment scoring and concise
summaries with identifiable sources and (2) key fundamental indicators with historical ratio visualizations.
Its core mechanism is a sentiment to fundamental linkage that converts news narratives into structured
verification prompts, delivered as a twosided cue (“Positive Reasons” versus “Potential Risks”). A
webbased prototype was demonstrated on Indonesian listed equities, with implementation evidence
reported through screenshots and a feature implementation matrix. The results show a stepwise
verification workflow that encourages users to consider supporting evidence and risks before forming
conclusions. This study contributes an integrated educational scaffold rather than a trading
recommendation and provides a replicable prototype concept and foundation for future userbased
effectiveness evaluation.