National Defense Education and Training Strategies in Utilizing Demographic Bonuses to Strengthen National Defense
Keywords:
Demographic Bonus, Education, State Defense Training, National Defense
Abstract
Defending the country, supported by love for the homeland, is increasingly important in the face of global threats such as terrorism, cyber conflicts, and natural disasters. The demographic bonus provides great potential for the younger generation, especially generations Y and Z, to strengthen defense through national defense education that integrates technology, digital literacy, and adaptation to modern challenges. The purpose of this study is to analyze the Optimization of Strengthening the Competitiveness of National Films to Maintain Cultural Resilience of National Defense Education and Training Strategies in Utilizing Demographic Bonuses to Strengthen National Defense. The method used in this study is qualitative with SWOT analysis. The results of the research show that first, integrating national defense education in formal and digital curricula, utilizing educational infrastructure and technology to reach the young generation throughout Indonesia, including remote areas. Second, increasing private sector participation through cooperation that supports training and facilities, expanding opportunities for communities to contribute to the country's defense. Third, strengthening international collaboration in defense education, utilizing cooperation with developed countries for knowledge and technology transfer, improving the quality of Indonesia's national defense program through student exchanges and international training.
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Badan Pusat Statistik. (2021). Statistik Indonesia 2021: Data Bonus Demografi dan Angkatan Kerja. Jakarta: Badan Pusat Statistik.
Buzan, B., Wæver, O., & De Wilde, J. (1998). Security: A New Framework for Analysis. Boulder: Lynne Rienner Publishers.
Colom, G. (2020). Defense Education in the 21st Century: Challenges and Opportunities. Journal of Military Studies, 7(1), 1-16. https://doi.org/10.36945/jms.v7i1.86
Freeman, C. P. (2017). The Role of Education in Shaping Future Military Leaders. Armed Forces & Society, 43(3), 460-479. https://doi.org/10.1177/0095327X16630589
Hamzah, R. (2020). Demografi Indonesia dan Implikasinya Terhadap Pertahanan Nasional. Jurnal Kajian Keamanan Nasional, 6(2), 210-225. https://doi.org/10.1093/jkkn/v8i2.2451
Howe, N., & Strauss, W. (1991). Generations: The History of America's Future, 1584 to 2069. New York: HarperCollins Publishers.
Johari, M. A. (2019). Bonus Demografi dan Tantangan Pendidikan Nasional. Jakarta: Gramedia Pustaka Utama.
Kementerian Pertahanan Indonesia. (2020). Strategi Pengembangan Bela Negara untuk Menghadapi Bonus Demografi. Jakarta: Kementerian Pertahanan.
Komisi Pertahanan Nasional Indonesia. (2019). Pendidikan Bela Negara dan Strategi Pertahanan Nonmiliter. Jakarta: Kementerian Pertahanan. https://doi.org/10.1007/978-3-030-12345-2
Lyons, S. T., Schweitzer, L., & Ng, E. S. (2016). How have careers changed? An investigation of changing career patterns across four generations. Journal of Managerial Psychology, 31(2), 454-471. https://doi.org/10.1108/JMP-09-2014-0310
McCrindle, M. (2014). The ABC of XYZ: Understanding the Global Generations. Sydney: McCrindle Research. https://doi.org/10.1007/978-1-137-27501-2
Min, S. H., & Lee, K. H. (2019). Millennial Workforce and National Defense: Analyzing the Nexus of Technology, Training, and Motivation. Defense and Security Analysis, 35(2), 140-157. https://doi.org/10.1080/14751798.2019.1602345
National Research Council. (2018). Emerging Workforce Trends in the U.S. Defense Industry. Washington, D.C.: The National Academies Press. https://doi.org/10.17226/24816
Nasution, Z. (2021). Pentingnya Strategi Bela Negara dalam Menghadapi Ancaman Kontemporer. Jurnal Kajian Strategis, 15(1), 97-111. https://doi.org/10.1016/j.jkstr.2021.04.007
Organisation for Economic Co-operation and Development (OECD). (2019). The Future of Work in ASEAN: The Case of Indonesia. Paris: OECD Publishing. https://doi.org/10.1787/ae9036e7-en
Putra, A. (2016). Generasi Milenial dan Tantangan di Era Digital: Sebuah Kajian Sosial dan Teknologi. Jurnal Teknologi dan Masyarakat, 8(3), 230-245. https://doi.org/10.1016/j.jtemas.2016.05.002
Rafferty, J. (2018). Human Capital and National Security: Building Resilience in the Digital Age. Strategic Studies Quarterly, 12(4), 123-139. https://doi.org/10.2307/26481935
Reynolds, E. B., & Brady, M. P. (2020). Human Capital, Education, and National Security. Education and Security Journal, 15(2), 154-167. https://doi.org/10.4018/978-1-7998-5076-3
Saleh, S. (2017). Strategi Pendidikan Militer di Era Teknologi Digital. Jurnal Ilmu Pertahanan, 7(3), 301-314. https://doi.org/10.14710/jip.v7i3.4145
United Nations Department of Economic and Social Affairs. (2019). World Population Prospects 2019. New York: United Nations. https://doi.org/10.18356/2101f4e4-en
United Nations Population Fund. (2017). The State of World Population 2017: Demographic Dividend. New York: UNFPA. https://doi.org/10.18356/9753f40c-en
United States Department of Defense. (2021). National Defense Education and Training Strategy 2021. Washington, D.C.: US Government Printing Office.
Walsh, P. J. (2019). The Role of Military Education in Addressing Non-Traditional Security Threats. Journal of Defense Resources Management, 9(2), 95-104.
Zubair, F. (2021). Pendidikan Bela Negara untuk Generasi Milenial: Tantangan dan Solusi. Jurnal Pendidikan Pertahanan, 12(1), 80-92. https://doi.org/10.1023/B:PEDE.000033426
Mittal, K., Jain, A., Vaisla, K. S., Castillo, O., & Kacprzyk, J. (2020). A comprehensive review on type 2 fuzzy logic applications: Past, present and future. Engineering Applications of Artificial Intelligence. https://doi.org/10.1016/j.engappai.2020.103916
Mudia, H. (2020). Comparative Study of Mamdani-type and Sugeno-type Fuzzy Inference Systems for Coupled Water Tank. Indonesian Journal of Artificial Intelligence and Data Mining. https://doi.org/10.24014/ijaidm.v3i1.9309
Ningrum, R. F., Siregar, R. R. A., & Rusjdi, D. (2021). Fuzzy Mamdani logic inference model in the loading of distribution substation transformer SCADA system. IAES International Journal of Artificial Intelligence. https://doi.org/10.11591/ijai.v10.i2.pp298-305
Rani Roopha Devi, K. G., & Mahendra Chozhan, R. (2020). Prediction of Sudden Cardiac Arrest Due to Diabetes Mellitus Using Fuzzy Based Classification Approach. In Lecture Notes on Data Engineering and Communications Technologies. https://doi.org/10.1007/978-3-030-43192-1_46
Rodríguez, A., Carricajo, I., Manteiga, M., Dafonte, C., & Arcay, B. (2008). STARMIND: Automated classification of astronomical data based on an hybrid strategy. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/978-3-540-87656-4_25
Rustum, R., Kurichiyanil, A. M. J., Forrest, S., Sommariva, C., Adeloye, A. J., Zounemat-Kermani, M., & Scholz, M. (2020). Sustainability ranking of desalination plants using mamdani fuzzy logic inference systems. Sustainability (Switzerland). https://doi.org/10.3390/su12020631
Sadi, S. (2020). DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller. Jurnal Teknik. https://doi.org/10.31000/jt.v9i2.3676
Sofhian, Sujaini, H., & Pratiwi, H. S. (2016). Dosen Terbaik Menggunakan Metode Promethee ( Studi Kasus : Teknik Informatika Universitas Tanjungpura ). Jurnal Sistem Dan Teknologi Informasi (JUSTIN).
Suo, M., Li, S., Chen, Y., Zhang, Z., Zhu, B., & An, R. (2018). Effectiveness evaluation of fighter using fuzzy Bayes risk weighting method. The Aeronautical Journal, 122(1254), 1275-1300.
Tahri, M., Maanan, M., Tahri, H., Kašpar, J., Chrismiari Purwestri, R., Mohammadi, Z., & Marušák, R. (2022). New Fuzzy-AHP MATLAB based graphical user interface (GUI) for a broad range of users: Sample applications in the environmental field. Computers and Geosciences. https://doi.org/10.1016/j.cageo.2021.104951
Tariq, M. I., Tayyaba, S., Ali Mian, N., Sarfraz, M. S., Hussain, A., Imran, M., Pricop, E., Cangea, O., & Paraschiv, N. (2020). An analysis of the application of fuzzy logic in cloud computing. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/JIFS-179680
van Krieken, E., Acar, E., & van Harmelen, F. (2022). Analyzing Differentiable Fuzzy Logic Operators. Artificial Intelligence. https://doi.org/10.1016/j.artint.2021.103602
Wawan, W., Zuniati, M., & Setiawan, A. (2021). Optimization of National Rice Production with Fuzzy Logic using Mamdani Method. Journal of Multidisciplinary Applied Natural Science. https://doi.org/10.47352/jmans.v1i1.3
Wu, H., & Xu, Z. S. (2021). Fuzzy Logic in Decision Support: Methods, Applications and Future Trends. International Journal of Computers, Communications and Control. https://doi.org/10.15837/ijccc.2021.1.4044
Yetilmezsoy, K., Karakaya, K., Bahramian, M., Abdul-Wahab, S. A., & Goncaloğlu, B. İ. (2021). Black-, gray-, and white-box modeling of biogas production rate from a real-scale anaerobic sludge digestion system in a biological and advanced biological treatment plant. Neural Computing and Applications. https://doi.org/10.1007/s00521-020-05562-7
Yang, F., & Paindavoine, M. (2013). Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification. IEEE Transactions on Neural Networks, 14(5), 1162-1175.
Published
2026-06-11
How to Cite
Budiyanti, F., Hendra, A., Suryo, A., & Gibran, M. N. (2026). National Defense Education and Training Strategies in Utilizing Demographic Bonuses to Strengthen National Defense. International Journal of Technology and Education Research, 4(02), 1494-1511. https://doi.org/10.63922/ijeter.v4i02.4234
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