DAGUSIBU untuk Desa Sehat: Edukasi Pengelolaan Obat yang Benar bagi Karang Taruna
Bibliographic record
Abstract
Rendahnya tingkat pemahaman masyarakat terkait cara memperoleh, menggunakan, menyimpan, dan membuang obat secara benar menjadi tantangan serius dalam menjaga kesehatan dan kelestarian lingkungan. Kegiatan Pengabdian Kepada Masyarakat ini bertujuan meningkatkan literasi pengelolaan obat yang aman di kalangan Karang Taruna Desa Ciputri melalui pendekatan edukasi berbasis komunitas dengan mengedepankan prinsip DAGUSIBU (Dapatkan, Gunakan, Simpan, dan Buang). Program dilaksanakan melalui sosialisasi interaktif, simulasi, serta pendampingan yang didukung dengan media edukasi cetak dan digital. Hasil kegiatan menunjukkan adanya peningkatan signifikan pengetahuan dan keterampilan peserta, terbentuknya kader Duta Literasi Obat, serta meningkatnya kesadaran masyarakat terhadap pentingnya pengelolaan obat yang tepat. Rekomendasi utama mencakup pendampingan berkelanjutan, penguatan peran perpustakaan sebagai pusat edukasi, serta kolaborasi lintas sektor guna memperluas jangkauan dan dampak edukasi ini.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.023 |
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".