Big Data Utilization in Port and Shipping Management Education: An Expert Validation Study

Abstract

Indonesian port and shipping management has entered a rapid data-driven transformation: the Inaportnet electronic port clearance system, container terminal operating systems, and logistics analytics platforms now constitute the operational data infrastructure within which port and shipping management graduates must work competently from their first professional appointments. Yet the degree to which STIP Jakarta's Port and Shipping Management curriculum equips cadets with the big data literacy and analytical competency these environments require has not been empirically validated against the assessments of practitioners who have directly experienced both historical curriculum outputs and current industry data demands. This study examines big data utilization competency gaps in PSM maritime education through an expert validation design involving 10 retired and active Port and Shipping Management practitioners from the STIP Jakarta expert community, using focus group discussion combined with systematic document triangulation of PSM curriculum materials. Four competency gap clusters were identified: Data Literacy Foundation (moderate curriculum coverage, expert-assessed as insufficient for industry demands), Logistics Analytics Application (low curriculum coverage, highest industry urgency), Platform and System Proficiency (minimal curriculum coverage, high and growing demand), and Data-Driven Decision Making (absent from curriculum, identified as the meta-competency gap most consequential for graduate employability). Document triangulation confirms that 0 of 12 PSM core module syllabi contain assessed big data competency learning outcomes. The study contributes the first expert-validated big data competency gap diagnostic for PSM maritime education in Indonesia and provides specific curriculum integration recommendations derived directly from practitioner demand evidence.