Peningkatan Kapasitas Petugas Vaksinator Melalui Kegiatan Refreshing dalam Implementasi Vaksin Baru: PCV, Rotavirus, dan HPV di Kabupaten Karanganyar dan Kabupaten Sukoharjo
Bibliographic record
Abstract
Imunisasi merupakan upaya preventif yang efektif dalam menurunkan angka kesakitan dan kematian akibat penyakit menular, terutama pada bayi dan balita. Dalam rangka mendukung program imunisasi nasional dan pencapaian Sustainable Development Goals (SDGs) 2030, pemerintah telah menambahkan tiga jenis vaksin baru, yakni Pneumococcal Conjugate Vaccine (PCV), Rotavirus, dan Human Papillomavirus (HPV). Implementasi vaksin baru menuntut kesiapan petugas vaksinator, baik dari segi pengetahuan, keterampilan teknis, hingga komunikasi efektif. Kegiatan pengabdian ini bertujuan untuk meningkatkan kapasitas vaksinator melalui pelatihan penyegaran (refreshing) di Kabupaten Karanganyar dan Kabupaten Sukoharjo. Metode pelaksanaan terbagi dua tahap, yaitu audiensi persiapan dan pelaksanaan kegiatan refreshing. Materi yang disampaikan dalam kegiatan refreshing meliputi informasi terkait vaksin baru, teknik penyuntikan yang aman (safety injection), dan komunikasi efektif. Kegiatan diikuti oleh 49 petugas vaksinator dari dua kabupaten. Hasil diskusi kelompok menunjukkan bahwa secara umum kesiapan sumber daya manusia dan logistik telah memadai, namun masih terdapat kendala seperti keterbatasan tenaga IT, keterlambatan distribusi vaksin, serta tantangan dalam penerimaan masyarakat akibat informasi yang salah. Program refreshing ini dinilai penting untuk memperbarui kompetensi vaksinator, memperkuat pelaksanaan imunisasi vaksin baru, dan meningkatkan mutu layanan imunisasi di tingkat puskesmas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".