Mapping the Scope of the Decision Support System (Ai-DSS) Decision Support System (Ai-DSS) Decision Function to the Decision Needs of the Universal Defense System: An Integrative Literature Review

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FORMOSA NEWS - Jakarta- Defense AI Models Fall Short of Indonesia’s Total Defense System Needs, Study Finds. Artificial intelligence decision support systems developed for military use remain heavily concentrated on battlefield tactics and operational command, creating a critical misalignment with comprehensive national defense frameworks like Indonesia’s Total People’s Defense System. This key insight comes from a study published in the Formosa Journal of Applied Sciences in July 2026 by researchers Cecep Rusdiana, Helda Risman, and Fauzia G. Cempaka Timur from the Universitas Pertahanan Republik Indonesia (Indonesian Defense University). The findings highlight a major gap in current defense technology: while AI systems excel at fast-paced tactical calculations, they fail to accommodate the multi-agency coordination, civil-military integration, and national resource mobilization required by broad-based national defense doctrines.

The Gap Between Tactical AI and National Defense Doctrines
Modern defense environments present complex, hybrid threats ranging from cyber warfare to widespread disinformation campaigns. To respond effectively, defense establishments increasingly rely on Artificial Intelligence-based Decision Support Systems (AI-DSS). These digital tools analyze large-scale datasets, run predictive simulations, and recommend courses of action to reduce cognitive strain on decision-makers. However, national defense in countries like Indonesia does not rely solely on active military forces. Indonesia’s defense framework known as Sishankamrata (Sistem Pertahanan dan Keamanan Rakyat Semesta) is anchored in law and presidential policy, mandating an all-inclusive defense posture that mobilizes civilian institutions, local governments, industrial resources, and general citizens alongside the armed forces. Existing defense AI literature focuses almost exclusively on conventional military structures. This imbalance raises a critical question for national security planners: can technologies built for tactical battlefields effectively support a nationwide, whole-of-society defense architecture?

Analyzing Global Defense AI Literature
To assess how well current defense AI matches universal defense requirements, Cecep Rusdiana, Helda Risman, and Fauzia G. Cempaka Timur from Universitas Pertahanan Republik Indonesia conducted an integrative literature review combined with directed content analysis. The research team analyzed 58 peer-reviewed full-text articles and technical reports on military AI-DSS published between 2018 and mid-2026. They evaluated each publication across six distinct structural dimensions:

• Decision Level: Strategic, operational, or tactical focus.
  
• Decision Function: Specific tasks such as command and control, planning, or logistics.
  
• Primary Decision User: Commanders, staff officers, analysts, or civilian officials.
  
• Organizational Scope: Single-service, joint military, interagency, or whole-of-society.
  
• Non-Military Actor Status: Role of civilians as data sources, system users, or equal decision-makers.
  
• Locus of Decision Authority: Centralized command versus decentralized authority across agencies.
  

To establish a clear benchmark, the researchers synthesized Indonesian defense laws (including Law No. 3/2002 and Law No. 23/2019), national defense doctrine, and Presidential Regulation No. 111/2025. This synthesis defined six core operational needs of a universal defense system: national resource mobilization, defense resource management, interagency civil-military coordination, territory-based defense, citizen participation, and component integration.

Key Research Findings
The empirical mapping revealed a heavy skew toward operational-level military command rather than broad governance functions:

• Operational Focus Dominates: Over 60.3% of analyzed articles (35 studies) focused on the operational level, compared to 25.9% on strategic decisions and 13.8% on tactical execution.
  
• Concentration on Battlefield Control: Battlefield Command and Control (C2) accounted for 39.7% of all studies (23 articles), while operational planning represented 19.0%. Together, these two functions comprised 89.5% of studies with a single dominant function.
  
• Omission of Mobilization Functions: Zero studies identified national mobilization or national resource allocation as their dominant decision function. Civil-military coordination appeared as a primary focus in only one study (1.7%).
  
• Military User Bias: Military commanders were designated as the primary user in 60.3% of the literature. Not a single study positioned civilian leaders or government agencies as primary decision-makers.
  
• Restricted Organizational Boundaries: Over 86.2% of AI-DSS models operated strictly within single-service or joint military bounds. Interagency applications represented just 12.1%, while whole-of-society models accounted for a single study (1.7%).
  
• Civilian Exclusion: Non-military actors were completely absent from the decision processes in 91.4% of the analyzed literature. In the few instances where civilians appeared, they functioned merely as data sources (5.2%) or output recipients (3.4%), never as equal decision-makers.
  

Real-World Impact and Policy Implications

The findings by the Universitas Pertahanan Republik Indonesia team identify two structural bottlenecks in defense technology development: a Decision-Support Gap and an Organizational Scope Gap. The Decision-Support Gap illustrates that current AI tools cannot manage non-kinetic defense needs such as civilian resource mobilization or regional logistics. The Organizational Scope Gap demonstrates that AI architectures remain siloed within conventional military command chains, ignoring the interagency dynamics required during national crises. These results offer actionable guidance for defense planners and technology developers. As nations modernize their command infrastructure through AI, procurement strategies must look beyond off-the-shelf tactical algorithms. Defense software must be architected to support multi-agency data sharing, legal mandates, and cross-sector accountability.

Author Profiles
Cecep Rusdiana, S.T., M.Si. is a researcher and academic at Universitas Pertahanan Republik Indonesia. His primary expertise spans defense technology, decision support systems, and defense strategy.
Dr. Helda Risman, M.Si. (Han) is a senior faculty member and researcher at Universitas Pertahanan Republik Indonesia. She specializes in defense strategy, national security policy, and crisis management.
Fauzia G. Cempaka Timur, S.I.P., M.A. is a researcher and lecturer at Universitas Pertahanan Republik Indonesia. Her academic focus includes defense governance, international security, and public policy analysis.

Source

Cecep Rusdiana, Helda Risman, Fauzia G. Cempaka Timur. Mapping the Scope of the Decision Support System (Ai-DSS) Decision Function to the Decision Needs of the Universal Defense System: An Integrative Literature Review. Formosa Journal of Applied Sciences (FJAS).  Vol. 5, No. 7, Tahun 2026 (Halaman 1605–1624).
DOI : https://doi.org/10.55927/fjas.v5i7.89
URL: https://journalfjas.my.id/index.php/fjas