Penerapan Portal PEDULI WNI dalam Upaya Perlindungan Warga Negara Indonesia di Luar Negeri
Bibliographic record
Abstract
Melindungi WNI merupakan amanat konstitusi. Upaya peningkatan pelindungan WNI dilaksanakan antara lain melalui pembangunan sistem pelindungan, termasuk melalui inovasi teknologi seperti Portal PEDULI WNI. Portal PEDULI WNI merupakan sistem yang memfasilitasi pendataan WNI di Luar Negeri melalui fitur lapor diri, serta memudahkan WNI untuk mengajukan layanan baik secara online, maupun booking online untuk datang langsung ke perwakilan, serta memudahkan WNI untuk mengajukan pengaduan secara mandiri langsung melalui aplikasi. Portal ini telah diterapkan di seluruh Perwakilan RI di luar negeri sejak Januari 2019. Program pengabdian kepada masyakarat yang dilakukan oleh para dosen dan mahasiswa Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Kristen Indonesia tanggal 6 September 2021 berupaya untuk meningkatkan pemahaman para pelajar Indonesia di Toronto terkait penggunaan Portal PEDULI WNI. Metode yang dilaksanakan dengan mengenalkan program melalui zoom dan interaksi tanya jawab serta penjelasan aplikasi secara daring. Diharapkan dengan adanya sosialisasi dan diseminasi ini, para pelajar Indonesia di Toronto akan mendapatkan pelayanan dan pelindungan dari Perwakilan Indonesia di Luar Negeri secara maksimal. Kata Kunci : Portal PEDULI WNI; Pelindungan WNI; Diplomasi
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.227 | 0.114 |
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".