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Design of Antasena: an AI-powered maritime surveillance and anomaly detection system for security decision support

IAES International Journal of Artificial Intelligence · Vol. 15 No. 1 (2026) · pp. 269–288

DOI
10.11591/ijai.v15.i1.pp269-288
ISSN
2252-8938, 2089-4872
Published
2026-02-01
Publisher
Institute of Advanced Engineering and Science
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Indonesia’s vast maritime territory faces serious challenges from illegal fishing, smuggling, and habitat destruction. To address these, the Indonesian Navy (TNI-AL) developed Antasena, an artificial intelligence (AI)-powered smart dashboard integrating automatic identification system (AIS) data, satellite imagery, and conservation metrics. Antasena leverages advanced anomaly detection algorithms, achieving 95.3% accuracy, 94.7% precision, 94.2% recall, and a 96.8% receiver operating characteristic-area under the curve (ROC-AUC) score in identifying vessel anomalies, including unauthorized fishing and smuggling activities. Using the analyze, design, develop, implement, and evaluate (ADDIE) framework, the system supports real-time maritime surveillance and biodiversity monitoring in conservation zones. The main contributions of this study include the development of a user-centric AI-based dashboard for maritime anomaly detection, the integration of multi-source data with machine learning models, and validation through operational field tests with maritime authorities. Antasena offers a scalable and effective solution to strengthen maritime security and protect Indonesia’s marine resources.

Keywords

Collaboration network of the authors

26 authors · 55 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Muhammad AlfianAffiliation unknown2
I Gusti Lanang Agung Oka Cahyadi PradiptaAffiliation unknown1
Ahmad SaikhuInstitut Teknologi Sepuluh Nopember1
Diana PurwitasariInstitut Teknologi Sepuluh Nopember1
Daniel SiahaanInstitut Teknologi Sepuluh Nopember1
Dian SaputraAffiliation unknown1
Esti YuniarAffiliation unknown1
Joko Lianto BulialiInstitut Teknologi Sepuluh Nopember1
Dwi SunaryonoInstitut Teknologi Sepuluh Nopember1
Hazna At ThooriqohInstitut Teknologi Sepuluh Nopember1
Tiara Nur AnnisaInstitut Teknologi Sepuluh Nopember1
Eka Alifia KusnantiInstitut Teknologi Sepuluh Nopember1
Lauretha Devi Fajar VantieInstitut Teknologi Sepuluh Nopember1
Ary Mazharuddin ShiddiqiInstitut Teknologi Sepuluh Nopember1
Muhammad Faisal FananiInstitut Teknologi Sepuluh Nopember1
Amelia Devi Putri AriyantoInstitut Teknologi Sepuluh Nopember1
Lutfiyatul †̃AzizahInstitut Teknologi Sepuluh Nopember1
Wahyu Fajar SetiawanAffiliation unknown1
Ilham Putra AriatamaAffiliation unknown1
Afif AmirullahAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Design of Antasena: an AI-powered maritime surveillance and  anomaly detection system for security decision support</dc:title>
	<dc:creator>Badrudin, Arif</dc:creator>
	<dc:creator>Sumantri, Siswo Hadi</dc:creator>
	<dc:creator>Gemilang Gultom, Rudy Agus</dc:creator>
	<dc:creator>Apriyanto, I Nengah Putra</dc:creator>
	<dc:creator>Yuhana, Umi Laili</dc:creator>
	<dc:creator>Ratnasari, Fitria Dwi</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Anomaly detection system; Antasena; Artificial intelligence; Powered maritime surveillance; Security decision support</dc:subject>
	<dc:description xml:lang="en-US">Indonesia’s vast maritime territory faces serious challenges from illegal fishing, smuggling, and habitat destruction. To address these, the Indonesian Navy (TNI-AL) developed Antasena, an artificial intelligence (AI)-powered smart dashboard integrating automatic identification system (AIS) data, satellite imagery, and conservation metrics. Antasena leverages advanced anomaly detection algorithms, achieving 95.3% accuracy, 94.7% precision, 94.2% recall, and a 96.8% receiver operating characteristic-area under the curve (ROC-AUC) score in identifying vessel anomalies, including unauthorized fishing and smuggling activities. Using the analyze, design, develop, implement, and evaluate (ADDIE) framework, the system supports real-time maritime surveillance and biodiversity monitoring in conservation zones. The main contributions of this study include the development of a user-centric AI-based dashboard for maritime anomaly detection, the integration of multi-source data with machine learning models, and validation through operational field tests with maritime authorities. Antasena offers a scalable and effective solution to strengthen maritime security and protect Indonesia’s marine resources.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2026-02-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/27721</dc:identifier>
	<dc:identifier>10.11591/ijai.v15.i1.pp269-288</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 15, No 1: February 2026; 269-288</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v15.i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/27721/14936</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Arif Badrudin, Siswo Hadi Sumantri, Rudy Agus Gemilang Gultom, I Nengah Putra Apriyanto,  Umi Laili Yuhana, Fitria Dwi Ratnasari</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>