AI Literacy and Adoption Readiness Among Maritime Cadets: A Cross-Major Comparison at STIP Jakarta

Abstract

The progressive integration of artificial intelligence into maritime operational systems — encompassing AI-assisted navigation decision support, predictive maintenance platforms, and machine-learning-based cargo optimization tools — demands that maritime cadets possess not only technical competency in conventional seamanship but the AI literacy and adoption readiness necessary to work effectively within intelligent operational environments. Yet empirical evidence on AI literacy and adoption readiness among Indonesian maritime cadets, differentiated by academic program specialization, remains unavailable. This study examines AI literacy and adoption readiness among 30 cadets at Sekolah Tinggi Ilmu Pelayaran (STIP) Jakarta across Port and Shipping Management (PSM), Deck Nautical (DN), and Engine (ENG) programs using a Technology Acceptance Model-based quantitative survey instrument. Significant between-major differences were found on Perceived Usefulness (F(2,27) = 4.18, p = .027), Behavioral Intention to Adopt AI (F(2,27) = 6.43, p = .005), and Prior Digital Exposure (F(2,27) = 3.94, p = .032). PSM cadets exhibited the highest adoption readiness, DN cadets the lowest, and ENG cadets were intermediate. The study establishes the first cross-major AI readiness baseline within a single Indonesian maritime academy and provides evidence-based priorities for differentiated AI literacy curriculum integration.