EVOLUSI DAN TREN RISET BIDANG NAVIGASI MARITIM CERDAS: ANALISIS CO-OCCURRENCE

Abstract

Maritime navigation plays a crucial role in global trade and logistics, increasingly supported by intelligent technologies such as artificial intelligence, sensors, Internet of Things (IoT), and autonomous systems. This study aims to map smart maritime navigation's evolution and research trends through a bibliometric analysis focusing on keyword co-occurrence. Using data from the Scopus database (2014–2025) and VOSviewer software, 2,927 author keywords were analysed, with 56 meeting the minimum threshold for visualisation. The results reveal seven main thematic clusters covering AI-based identification systems, autonomous ship technologies, e-navigation, IoT integration, and satellite-based positioning. The overlay visualisation shows that recent research trends have shifted toward LiDAR, object detection, deep learning, and unmanned surface vehicles. These emerging themes highlight transitioning from conventional navigation systems to more automated, intelligent, and adaptive technologies. This study contributes to a better understanding of the knowledge structure in the field and provides strategic insights for future research directions and innovation planning in smart maritime navigation.