학술논문

The Prospect of Using Artificial Intelligence in TNI Ship Information Systems as a Manifestation of a Resilient Maritime Defense Industry
Document Type
article
Source
International Journal of Humanities Education and Social Sciences, Vol 3, Iss 3 (2023)
Subject
History of scholarship and learning. The humanities
AZ20-999
Social Sciences
Language
English
ISSN
2808-1765
Abstract
This research investigates the prospects of using Artificial Intelligence (AI) in the Indonesian Navy's ship information system as a crucial step in developing a robust and innovative maritime defense industry. The primary focus is on the application of AI technology in the ship information system, analyzing various aspects, including the potential implementation of AI in monitoring and analyzing maritime waters, technical and security challenges that may arise, expected benefits, and the strategic impact of AI implementation in Indonesia's maritime defense industry. The research method employs the Systematic Literature Review (SLR) method, providing a systematic and comprehensive approach to collecting, evaluating, and analyzing relevant literature in a specific field. This study involves literature searches using keywords such as artificial intelligence, information systems, maritime defense industry, Indonesian defense, and Indonesian Navy ships from 2011 to 2023 in various sources such as scholarly journals, conferences, and online databases. The research findings indicate that the use of artificial intelligence in the Indonesian Navy's ship information system has significant potential to improve maritime monitoring, threat detection, operational efficiency, and international collaboration. The integration of AI with advanced sensors such as radar, sonar, and thermal cameras enables more accurate real-time monitoring of activities in maritime waters. Higher accuracy in monitoring and threat detection also contributes to increased situational awareness and smarter decision-making by operational leaders in the Indonesian Navy. Despite the substantial benefits, AI implementation faces several challenges, including initial investment costs, infrastructure availability, personnel training, data security, ethical regulations, dependence on foreign technology, integration and compatibility issues, AI technology reliability, cultural and organizational changes, and long-term benefits. To address these challenges, it is recommended that the government allocates budgets wisely, develops adequate technological infrastructure, provides personnel training, and formulates ethical regulations. Strengthening independence in the development of domestic AI technology is also crucial.