Pembakuan Nama Pulau di Indonesia Sebagai Upaya untuk Menjaga Kedaulatan Negara Republik Indonesia
Bibliographic record
Abstract
Pada tahun 1987 dalam Konferensi Standarisasi Nama-Nama Geografi di Montreal, Kanada, Pemerintah Indonesia menyampaikan laporan ke PBB bahwa pulau-pulau di Indonesia telah bertambah dari 13.667 menjadi 17.508 buah. Pada saat itu PBB meminta Pemerintah Indonesia untuk menyampaikan daftar nama-nama pulau tersebut ke PBB. Data bulan Desember tahun 2007 dilaporkan bahwa dari 17.504 pulau yang tersebar di penjuru wilayah Indonesia, hanya 6.900 pulau yang memiliki nama yang telah dibakukan sesuai dengan standar internasional, selebihnya masih belum mempunyai nama yang diakui secara internasional. Penelitian ini bertujuan untuk menganalisis urgensi dilakukannya pembakuan nama bagi pulau-pulau di Indonesia sesuai dengan aturan hukum internasional serta upaya yang dilakukan oleh Pemerintah dalam membakuan nama pulau di Indonesia. Hasil penelitian ini menunjukkan bahwa upaya pembakuan nama pulau di Indonesia wajib dilakukan agar pulau-pulau yang merupakan bagian dari wilayah kedaulatan Indonesia, secara de jure, mendapatkan pengakuan internasional. Meskipun demikian terdapat kendala yang dihadapi oleh pemerintah Indonesia dalam melakukan pembakuan nama pulau seperti, kurangnya koordinasi antara aparat yang terkait, jumlah suku bangsa serta bahasa daerah yang beragam serta dana yang terbatas. In the year 1987, Government of Indonesia submitted a list reporting the increasing amount of island from 13.667 to 17.508 when attending United Nations Conference on Standardization of Geographical Names (UNCSGN) in Montreal, Canada. At that time, United Nations asked Indonesian Government to submit list of the islands to United Nations. Based on December 2007 data, reported that, from 17.504 islands scattered all around, only 6900 islands has name standardization in accordance with international standard. While the rest around 10.600 islands without standardization name, which is internationally recognized. The purpose of this research is to analyze the urgency of name standardization for Indonesia’s islands in accordance with the rules of international law. The result of this research shows that the efforts in standardization of island names in Indonesia ought to do, so that the remaining islands that become a part of Indonesian territory. However, there are few constraints faced by Indonesian government in conducting islands names standardization, such as: lack of coordination between relevant authorities, various numbers of tribes and local languages and limited funds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".