Machine learning deployment for arms dynamics pattern recognition in Southeast Asia region
Finding the most significant determinant variable of arms dynamic is highly required due to strategic policies formulations and power mapping for academics and policy makers. Machine learning is still new or underdiscussed among the study of politics and international relations. Existing literature...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2021-09-01.
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| Online Access: | Get fulltext |
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| LEADER | 02653 am a22003253u 4500 | ||
|---|---|---|---|
| 001 | ijeecs25849_15451 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Indra, Zul |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Setiawan, Azhari |e author |
| 700 | 1 | 0 | |a Jusman, Yessi |e author |
| 700 | 1 | 0 | |a Adnan, Arisman |e author |
| 245 | 0 | 0 | |a Machine learning deployment for arms dynamics pattern recognition in Southeast Asia region |
| 260 | |b Institute of Advanced Engineering and Science, |c 2021-09-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25849 | ||
| 520 | |a Finding the most significant determinant variable of arms dynamic is highly required due to strategic policies formulations and power mapping for academics and policy makers. Machine learning is still new or underdiscussed among the study of politics and international relations. Existing literature have much focus on using advanced quantitative methods by applying various types of regression analysis. This study analyzed the arms dynamic in Southeast Asia countries along with its some strategic partners such as United States, China, Russia, South Korea, and Japan by using 'Decision Tree' of machine learning algorithm. This study conducted a machine learning analysis on 55 variable items which is classified into 8 classes of variables videlicet defense budget, arms trade exports, arms trade imports, political posture, economic posture, security posture and defense priority, national capability, and direct contact,. The results suggest three findings: (1) state who perceives maritime as strategic drivers and forces will seek more power for its maritime defense posture which is translated to defense budget, (2) big size countries tend to be an arms exporter country, and (3) state's energy dependence often leads to a higher volume of arms transfers between countries. | ||
| 540 | |a Copyright (c) 2021 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Arms dynamics; Decision tree; Machine learning; Pattern recognition; Preprocessing; Southeast Asia; | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 23, No 3: September 2021; 1654-1662 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v23.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25849/15451 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25849/15451 |z Get fulltext |