Aplikasi Smart City - Governance : Teknologi Pelaporan Tempat Kejadian Perkara Sinkronisasi Sistem Informasi Geografis Secara Real Time
Bibliographic record
Abstract
Aplikasi smart city pelaporan TKP ini akan mewadahi masyarakat untuk ikut terlibat dalam melaporkan setiap kejadian perkara yang ditemukan dengan mengambil gambar melalui camera smartphone selanjutnya diunggah. Lokasi tempat mengunggah tersebut akan ditandai untuk sinkronisasi dengan teknologi sistem informasi geografis yang terlapor kepada pihak kepolisian secara langsung mendapatkan data dan lokasi kejadian secara real time dan akurat. Dalam teknologi smart city ini nantinya setiap laporan yang disampaikan oleh masyarakat akan termonitoring baik di polres ataupun di polsek-polsek, sehingga akan dengan mudah menentukan siapa yang paling dekat dari lokasi kejadian maka dialah yang ditugaskan untuk penanganan. Selain itu, dalam sistem juga akan dibaca lokasi-lokasi puskesmas maupun puskesmas pembantu sebagai alternatif pertama untuk pertolongan.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".