SELECTION OF UNMANNED AIRCRAFT VEHICLE (UAV) TO IMPROVE EARLY DETECTION IN SUPPORTING SECURITY OPERATIONS IN THE NATUNA SEA BASED ON MEASURE OF EFFECTIVENESS

Ady Nugroho, Victor Pardamean, M.B. Pandjaitan, Ardian Widjanarko D.S

Abstract


Technological developments in addition to bringing positive impacts also have negative impacts in the form of factual threats and potential threats to Indonesian marine security. The ability to detect and prevent early against these threats absolutely must be mastered by security and defense institutions or institutions in the marine sector. One of the efforts in collecting maritime data is to utilize Unmanned Aircraft Vehicle (UAV) technology. UAV technology has developed rapidly and is widely used in civilian and military circles, such as: early detection, intelligence surveillance and reconnaissance (ISR), image and video capture, Search and Rescue (SAR), and various reconnaissance and monitoring missions. The Indonesian Navy as a state instrument carrying out the task of state defense at sea has maritime operations capabilities that must continue to be developed. This study uses a descriptive quantitative approach, with the MoE method to assess the effectiveness of the use of UAV in Indonesian Navy intelligence and the AHP method to select the best type of UAV. The results of the effectiveness measurement obtained by UAV are declared effective in supporting the Navy's security operations. The results of data processing for the selection of the best UAV which is ranked first recommended to be held is the UAV type of High Altitude Long Endurance (HALE) which has strategic capabilities. It is hoped that by having UAV type HALE the TNI Al's operational pattern will be more effective and security can be increased optimally

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References


Andress, J., & Winterfeld, S. (2014). Cyber Doctrine. In Cyber Warfare (2nd ed., pp. 53–82). Elsevier Inc. https://doi.org/10.1016/B978-0-12-416672-1.00004-0

Custers, B. (2016). Drones Here , There and Everywhere Introduction and Overview. In The Future of Drone Use (pp. 3–20). WODC, Research Center of the Ministry of Security and Justice. https://doi.org/10.1007/978-94-6265-132-6

Dimitriou, G. (2013). Integrating unmanned aerial vehicles into surveillance systems in complex maritime environments (Issue September). Naval Postgraduate School.

Jeon, I., Ham, S., Cheon, J., Klimkowska, A. M., Kim, H., Choi, K., & Lee, I. (2019). A REAL-TIME DRONE MAPPING PLATFORM FOR MARINE SURVEILLANCE. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W13, 2019 ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands A, XLII(June), 10–14.

Liang, H., Ren, J., Gao, S., & Dong, L. (2017). Comparison of Different Multicriteria Decision-Making Methodologies for Sustainability Decision Making. In Hydrogen Economy. Elsevier Ltd. https://doi.org/10.1016/B978-0-12-811132-1.00008-0

Melillos, G., Themistocleous, Kyriacos, Michaelides, Silas, Hadjimitsis, & Diofantos. (2020). The use of remote sensing for maritime surveillance for security and safety in Cyprus. Proc. SPIE 11418, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXV, April. https://doi.org/10.1117/12.2567102

Oliveau, Q. (2019). Ship classification for maritime surveillance. IEEE Explore, 1–5.

Qazi, W. A., & Abushammala, M. F. M. (2020). of waste-to-energy technologies. In Waste-to-Energy. INC. https://doi.org/10.1016/B978-0-12-816394-8.00010-0

Saaty, T. L. (2008). Decision making with the analytic hierarchy process Decision making with the analytic hierarchy process. Int. J. Services Sciences, 1(1), 83–98. https://doi.org/10.1504/IJSSCI.2008.017590

Singh, M., Khare, S., & Kaushik, B. K. (2020). Performance Improvement of Electro-Optic Search and Track System for Maritime Surveillance. 70(1), 66–71.

Soldi, G., Gaglione, D., Forti, N., Simone, A. Di, Daffin, F. C., Bottini, G., & Quattrociocchi, D. (2020). Space-based Global Maritime Surveillance . Part II : Artificial Intelligence and Data Fusion Techniques. IEEE Aerospace and Electronic Systems Magazine, November 2020. https://doi.org/10.1109/MAES.2021.3070884

Soldi, G., Gaglione, D., Forti, N., Simone, A. Di, Daffin, F. C., Bottini, G., Quattrociocchi, D., Millefiori, L. M., Braca, P., Carniel, S., Willett, P., & Iodice, A. (2020). Space-based Global Maritime Surveillance . Part I : Satellite Technologies. Electrical Engineering and Systems Science, 1–26.

Srinivasan, K., Ramaneswaran, S., S, S. K., & Narayanan, S. (2019). Aerial and Under-water Dronal Communication : Potentials , Issues and Vulnerabilities. International Journal of Innovative Technology and Explorinag Engineering (IJITEE), 9(1), 3874–3885. https://doi.org/10.35940/ijitee.A4958.119119

Suteris, M. S., Rahman, F. A., & Ismail, A. (2018). Route Schedule Optimization Method of Unmanned Aerial Vehicle Implementation for Maritime Surveillance in Monitoring Trawler Activities in Kuala Kedah , Malaysia. International Journal of Supply Chain Management, 7(5), 245–249.

Wen, R., Yuan, W., Chen, X., & Lu, Y. (2021). An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system. Ocean Engineering, 235(June), 109435. https://doi.org/10.1016/j.oceaneng.2021.109435

West, J. P., & Bowman, J. S. (2022). The Domestic Use of Drones : An Ethical Analysis of Surveillance Issues. Public Administration Review, 76(4), 649–659. https://doi.org/10.1111/puar.12506.against

Zhang, B., Shen, X., Wang, J., & Chen, Y. (2013). Measurement of Effectiveness of Software Testing. In Y. Wang & L. Tan (Eds.), Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing (Vol. 8783, Issue Icmv 2012, pp. 1–6). https://doi.org/10.1117/12.2021253




DOI: https://doi.org/10.24114/tgeo.v11i1.34932

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