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

Cecep Rusdiana; Helda Risman; Fauzia G. Cempaka Timur

doi:10.55927/fjas.v5i7.89

Authors

Cecep Rusdiana Universitas Pertahanan Republik Indonesia
Helda Risman Universitas Pertahanan Republik Indonesia
Fauzia G. Cempaka Timur Universitas Pertahanan Republik Indonesia

DOI:

https://doi.org/10.55927/fjas.v5i7.89

Keywords:

AI-DSS, Decision Support Systems, Defense Decision-Making, Sishankamrata, Total Defense

Abstract

This study maps the decision-support and organizational coverage of Artificial Intelligence-based Decision Support Systems (AI-DSS) in defense literature and compares it with six core decision requirements of Indonesia’s Total People’s Defense System (Sishankamrata). Using an Integrative Literature Review and directed content analysis, 58 full-text defense AI-DSS articles were coded across six dimensions: decision level, decision function, primary decision user, organizational scope, non-military actor status, and locus of decision authority. The benchmark was developed independently through a structured synthesis of Indonesian defense laws, doctrine, and current policy. The findings show that AI-DSS literature is concentrated at the operational level (60.3%), particularly in Battlefield/C2 (39.7%) and operational planning (19.0%). National mobilization and national resource allocation were not identified as dominant functions, while civil–military coordination appeared in one article (1.7%).

References

Adkins, A. K. (2025, January–February). Achieving decision dominance: The arduous pursuit of operationalized data. Military Review, 86–95.

Andersin, E. (2025). The use of the ‘Lavender’ in Gaza and the law of targeting: AI-decision support systems and facial recognition technology. Journal of International Humanitarian Legal Studies, 16(2), 336–370. https://doi.org/10.1163/18781527-bja10119.

Ångström, J., & Ljungkvist, K. (2024). Unpacking the varying strategic logics of total defence. Journal of Strategic Studies, 47(4), 498–522. https://doi.org/10.1080/01402390.2023.2260958.

Boyd, J. R. (2018). A discourse on winning and losing (G. T. Hammond, Ed. & Comp.). Air University Press.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa.

Devitt, S. K., Scholz, J., Schless, T., & Lewis, L. (2023). Developing a trusted human-AI network for humanitarian benefit. Digital War, 4, 1–17. https://doi.org/10.1057/s42984-023-00063-y.

Djansena, A., Supriyadi, A. A., Kartiningsih, Y., Yusman, F., & Saleh, B. R. (2025). Strengthening Indonesia’s defense capability through AI-driven decision-making. Jurnal Praksis dan Dedikasi Sosial, 8(2), 361–377. https://doi.org/10.17977/um022v8i22025p361-377.

Goecks, V. G., & Waytowich, N. (2024). COA-GPT: Generative pre-trained transformers for accelerated course of action development in military operations [Preprint]. arXiv. https://arxiv.org/abs/2402.01786.

Gorry, G. A., & Scott Morton, M. S. (1971). A framework for management information systems. Sloan Management Review, 13(1), 55–70.

Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59–82. https://doi.org/10.1177/1525822X05279903.

Hoffman, W., & Kim, H. M. (2023). Reducing the risks of artificial intelligence for military decision advantage [Policy brief]. Center for Security and Emerging Technology, Georgetown University.

Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687.

Johnson, J. (2022). The AI commander problem: Ethical, political, and psychological dilemmas of human-machine interactions in AI-enabled warfare. Journal of Military Ethics, 21(3–4), 246–271. https://doi.org/10.1080/15027570.2023.2175887.

Johnson, J. (2023). Automating the OODA loop in the age of intelligent machines: Reaffirming the role of humans in command-and-control decision-making in the digital age. Defence Studies, 23(1), 43–67. https://doi.org/10.1080/14702436.2022.2102486.

Johnson, J. (2026). Can AI behave ethically during military crises? Preserving human moral agency. International Affairs, 102(1), 63–83. https://doi.org/10.1093/ia/iiaf191.

Klonowska, K. (2022). Article 36: Review of AI decision-support systems and other emerging technologies of warfare. In T. D. Gill, R. Geiß, H. Krieger, & R. Mignot-Mahdavi (Eds.), Yearbook of International Humanitarian Law, Volume 23 (2020) (pp. 123–153). T.M.C. Asser Press. https://doi.org/10.1007/978-94-6265-491-4_6.

Lee, J., Eom, C., Kim, C., Kim, K., Lee, H., Kang, H., & Kwon, M. (2026). AI fire support officer: Military decision support system based on reward adaptive reinforcement learning. Journal of the Korean Institute of Communications and Information Sciences, 51(1), 209–222. https://doi.org/10.7840/kics.2026.51.1.209.

Lushenko, P. (2025). AI, trust, and the war room: Evidence from a conjoint experiment in the US military. Cambridge Forum on AI: Law and Governance, 1, Article e52. https://doi.org/10.1017/cfl.2025.10019.

Maathuis, C., & Cools, K. (2025). Collateral damage assessment model for AI system target engagement in military operations. In MILCOM 2025-2025 IEEE Military Communications Conference (pp. 170–175). IEEE. https://doi.org/10.1109/MILCOM64451.2025.11310546.

Matthews, R., & Bintang Timur, F. (2024). Singapore’s ‘total defence’ strategy. Defence and Peace Economics, 35(5), 638–658. https://doi.org/10.1080/10242694.2023.2187924.

Mayer, M. (2023). Trusting machine intelligence: Artificial intelligence and human-autonomy teaming in military operations. Defense & Security Analysis, 39(4), 521–538.

Osinga, F. P. B. (2007). Science, strategy and war: The strategic theory of John Boyd. Routledge.

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71.

Pollock, K., & Steen, R. (2021). Total defence resilience: Viable or not during COVID-19? A comparative study of Norway and the UK. Risk, Hazards & Crisis in Public Policy, 12(1), 73–109. https://doi.org/10.1002/rhc3.12207.

Probasco, E. S., Toner, H., Burtell, M., & Rudner, T. G. J. (2025). AI for military decision-making: Harnessing the advantages and avoiding the risks [Issue brief]. Center for Security and Emerging Technology, Georgetown University. https://doi.org/10.51593/20240028.

Ramadhianto, R., Toruan, T. S. L., Kertopati, S. N. H., & Almubaroq, H. Z. (2023). Implementation of artificial intelligence on Indonesia’s defense intelligence activities. Jurnal Pertahanan, 9(2), 350–365.

Republik Indonesia. (2002). Undang-Undang Republik Indonesia Nomor 3 Tahun 2002 tentang Pertahanan Negara. Lembaran Negara Republik Indonesia Tahun 2002 Nomor 3.

Republik Indonesia. (2019). Undang-Undang Republik Indonesia Nomor 23 Tahun 2019 tentang Pengelolaan Sumber Daya Nasional untuk Pertahanan Negara. Lembaran Negara Republik Indonesia Tahun 2019 Nomor 211.

Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality & Quantity, 52, 1893–1907. https://doi.org/10.1007/s11135-017-0574-8.

Spahr, T. W. (2024). Raven Sentry: Employing AI for indications and warnings in Afghanistan. Parameters, 54(2), 95–109. https://doi.org/10.55540/0031-1723.3289.

Torraco, R. J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4(3), 356–367. https://doi.org/10.1177/1534484305278283.

Tóth, A. (2025). Enhancing situational awareness and decision-making: The impact of advanced ISR solutions on command and control systems. Hadmérnök, 20(2), 143–160. https://doi.org/10.32567/hm.2025.2.9.