MétaCan
Menu
Back to cohort
Record W4288462948 · doi:10.36049/genitri.v1i1.63

Edukasi Mengenai Hygiene Sanitasi Pada Pedagang Jamu di Kota Tanjungpinang

2022· article· id· W4288462948 on OpenAlexaff
Luh Pitriyanti

Bibliographic record

VenueGenitri Jurnal Pengabdian Masyarakat Bidang Kesehatan · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesHygieneBiologyMedicineArt

Abstract

fetched live from OpenAlex

Foodborne Disease disebabkan oleh cemaran biologis dari adanya kontaminasi pangan yang disebabkan cacing, parasit, bakteri (mikroba), fungi, virus dan riketsia. Jamu merupakan salah satu minuman tradisional yang memiliki risiko untuk tercemar sehingga menimbulkan foodborne Disease. Beberapa keterbatasan dalam pengolahan jamu adalah kurangnya kebersihan dan sanitasi (baik bahan baku, peralatan, maupun pembuat jamu itu sendiri), sehingga banyak ditemukan jamu yang kurang bersih dan dapat mengganggu kesehatan konsumen. Metode kegiatan pengabdian masyarakat ini dengan melakukan edukasi berupa penyuluhan perorangan menggunakan leaflet mengenai hygiene sanitasi bagi pedagang jamu yang ada di Kota Tanjungpinang. Hasil yang diperoleh dari kegiatan ini adalah berhasil dilakukan penyuluhaan personal kepada 8 pedagang jamu yang berada di Kota Tanjungpinang. Kegiatan edukasi dilakukan pada tanggal 27 - 30 Juni 2020 dan mendapatkan tanggapan positif dari seluruh peserta. Materi yang diberikan disampaikan dengan media leaflet agar mempermudah pemahaman pedagang mengenai hygiene sanitasi pedagang jamu. Saran dari kegiatan ini adalah kegiatan edukasi dapat dilakukan pada ranah yang lebih luas untuk seluruh pedagang jamu yang ada di Kota Tanjungpinang dan dilakukan pelatihan hygiene sanitasi untuk penjamah makanan sehingga meningkatkan kualitas minuman jamu yang ada di masyarakat.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0070.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0180.002

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.

Opus teacher head0.036
GPT teacher head0.320
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGenitri Jurnal Pengabdian Masyarakat Bidang KesehatanSame topicCOVID-19 Prevention and ImpactFrench-language works237,207