PENINGKATAN KERJA SAMA MILITER ANTARA TENTARA NASIONAL INDONESIA (TNI) DENGAN CANADIAN ARMED FORCES (CAF) DALAM UPAYA MENDUKUNG SASARAN STRATEGIS PERTAHANAN NEGARA
Bibliographic record
Abstract
Berubahnya tatanan internasional akibat globalisasi dan faktor-faktor lainnya kemudian mengakibatkan munculnya ancaman yang semakin kompleks. Interaksi antar negara dalam hubungan internasional kemudian bergeser dari saling curiga menjadi saling ketergantungan, hal ini dibuktikan dengan pola interaksi baru yakni kerja sama internasional. Kerja sama internasional sejatinya dilaksanakan untuk mendukung kepentingan nasional negara, khususnya di bidang pertahanan. Kerja sama internasional tidak terlepas dari proses Diplomasi sehingga Diplomasi Pertahanan adalah cara yang digunakan dalam upaya melakukan kerja sama internasional di bidang pertahanan dan militer. Dalam jurnal ini penulis akan menganalisis peningkatan kerja sama khususnya di bidang militer antara TNI dengan Canadian Armed Forces (CAF) dalam upaya mendukung kepentingan nasional yang tertuang di Sasaran Strategis Pertahanan Negara. Penulis menggunakan metode penelitian kualitatif yakni studi pustaka, dengan hasil analisis berupa peningkatan kerja sama militer antara TNI dengan CAF selaras dengan kepentingan nasional serta tujuan Indonesia yang tertuang di Buku Putih Pertahanan hingga Peraturan Panglima TNI No. 42 Tahun 2017 tentang Kerja Sama Internasional di Lingkungan TNI. Selain itu peningkatan kerja sama militer antara TNI dengan CAF juga dapat mendukung upaya pencapaian kepentingan nasional Indonesia yang dikemas dalam Sasaran Strategis Pertahanan Negara.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".