Sosialisasi dan Edukasi Panduan Bersih Sehat Makan Diluar Pada UMKM Kuliner
Bibliographic record
Abstract
UMKM Kuliner merupakan salah satu UMKM yang menurun kinerjanya di masa pandemi COVID- 19. Salah satu cara untuk meningkatkan kinerja UMKM Kuliner adalah menerap proses pengolahan dan penyajian produk makanan dan minuman UMKM yang aman, bersih, dan sehat, sehingga masyarakat tidak perlu khawatir untuk membeli. Oleh karena itu, dibuatlah panduan Bersih Sehat Aman Makan Di Luar (BSAMDL) agar pelaku UMKM Kuliner mudah untuk mempelajari dan mengimplementasikan dalam kegiatan operasional. Oleh karena itu, dilaksanakan kegiatan sosialisasi dan edukasi yang ditujukan bagi UMKM Kuliner mengenai panduan BSAMDL dengan peserta UMKM Kuliner di wilayah Jabodetabek yang bertujuan untuk memberikan pengetahuan mengenai bersih sehat aman makan di luar baik bagi para Pelaku UMKM Kuliner dan memberikan pengetahuan tatacara untuk mendapatkan sertifikat CHSE dari Kementerian Pariwisata dan Ekonomi Kreatif. Kegiatan sosialisasi dan edukasi ini dilakukan melalui media online dan diikuti oleh 40 pelaku UMKM kuliner. Hasil evaluasi menunjukkan bahwa setelah dilakukan kegiatan sosialisasi dan edukasi maka pelaku UMKM Kuliner menyadari pentingnya panduan bersih sehat dan aman makan di luar serta akan mengimplementasikan di tempat usaha.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.009 |
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".