Model Kuantitatif Indeks Pertahanan Nasional Berbasis Dynamic System dan RFAHP - Resti Oktaviani; Yanif Dwi Kuntjoro; Eltanin Lionel Purba (Badan Pendidikan dan Pelatihan Kementerian Pertahanan, 2026)
The modeling of the National Defense Index is conducted to produce a measurement system that is objective, quantifiable, transparent, and adaptive to the dynamics of emerging threats. This study aims to develop a quantitative National Defense Index model based on a Dynamic System approach and the Robust Fuzzy Analytical Hierarchy Process. The development of this model is motivated by the absence of a mathematically grounded measurement framework capable of representing the condition of national defense while supporting policy evaluation and strategic decision-making.The Robust Fuzzy Analytical Hierarchy Process method is employed to address uncertainty, subjectivity, and complexity in the multi-criteria weighting process, while the Dynamic System approach is utilized to capture the continuous evolution of defense conditions. The research data were obtained from assessments by approximately 10 respondents across more than 150 sub-criteria derived from three primary defense dimensions: national sovereignty, territorial integrity, and national security. The research procedure includes the identification of criteria and sub-criteria, determination of weights, data collection, score calculation, and index aggregation. The results indicate that the proposed model is capable of generating a more representative, structured, and applicable numerical measure for assessing national defense conditions. Based on simulation results, the National Defense Index value is 0.604531081, which falls within the moderate category. This finding suggests that the current national defense condition still requires strengthening in several strategic aspects. Therefore, the developed National Defense Index model can serve as a decision-support tool for policy evaluation, budget planning, personnel needs assessment, and the development of defense systems in a more measurable and adaptive manner.