Farah Mufida Qotrunnada, Setiyo Budiyanto, Achmad Farid Wadjdi

Predictive Analysis of The National Defense Index (IBN) on National Resilience Using Classification and Regression Trees (CART) Method

Introduction

Predictive analysis of the national defense index (ibn) on national resilience using classification and regression trees (cart) method . Predict national resilience using the National Defense Index (IBN) & CART method. Understand key factors for strengthening resilience and inform strategic policies for Indonesia Emas 2045.

Abstract

IBN (National Defense Index) is an important indicator in measuring public awareness and participation in maintaining the sovereignty and stability of the country. With the increasing complexity of challenges to national resilience, a predictive approach is needed to understand the relationship between IBN and other variables that influence national resilience. The CART method is used to identify patterns and determine significant variables that play a role in strengthening national resilience. Through this model, the study aims to provide deeper insight for the formulation of more effective policies in building strong national resilience. The results of the study were obtained by identifying factors that influence the National Defense Index (IBN). The results of this study are expected to be a consideration for the basis for strategic policies in achieving the great goal of Indonesia Emas 2045 as a strong, sovereign, and sustainable country.

Review

This paper addresses a highly pertinent and critical issue concerning national resilience, a fundamental aspect of a nation's security and stability. The focus on the National Defense Index (IBN) as a key indicator and its predictive power on national resilience is timely, especially in the context of increasing global complexities and the strategic objectives of Indonesia Emas 2045. The abstract clearly articulates the need for a data-driven predictive approach to inform policy, underscoring the potential real-world impact and relevance of the study's findings to national security and policy development. The application of the Classification and Regression Trees (CART) method is a sound choice for identifying non-linear patterns and significant variables within complex datasets, which is appropriate for socio-political indicators like IBN and national resilience. The stated aim to provide deeper insights for effective policy formulation is a significant strength. However, the abstract introduces a slight ambiguity regarding the precise role of IBN in the predictive model. While the title suggests IBN *predicts* national resilience, the abstract later mentions "identifying factors that influence the National Defense Index (IBN)." Clarifying whether IBN is the primary independent variable *predicting* national resilience, or if the study also involves *explaining* IBN itself, would enhance the clarity of the study's scope and methodology. Further detail on the operationalization of "national resilience" and the "other variables" considered in the CART model would also be beneficial for assessing the robustness of the proposed analysis. The potential policy implications of this research are substantial, promising to serve as a vital consideration for strategic policies aimed at achieving national goals such as a strong, sovereign, and sustainable Indonesia. To fully realize this potential, the complete paper should elaborate on the specific datasets used, the validation strategies employed for the CART model, and the detailed findings regarding which variables are truly significant. Providing concrete examples of how the identified patterns or significant variables translate into actionable policy recommendations would significantly strengthen the paper's contribution. Overall, this study presents a valuable and relevant endeavor, and with clearer exposition on its methodological specifics and detailed findings, it holds strong promise for contributing meaningfully to the field of national security and policy formulation.

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