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Record W4361244655 · doi:10.25157/ag.v5i1.10005

EDUKASI DAN PENDAMPINGAN KEGIATAN PRODUKSI SAMILER DALAM UPAYA MENINGKATKAN MUTU PRODUKSI DAN PEMASARAN DIGITAL

2023· article· id· W4361244655 on OpenAlexaff
Septi Budi Sartika, Ardent Dhamar Kenda, Raden Muhammad Syamsul Huda, Arbiya Maghfiroh Rohmi, Isnaini Dwi Aprillia

Bibliographic record

VenueAbdimas Galuh · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Kegiatan pengabdian ini bertujuan untuk memberikan edukasi dan pendampingan dalam kegiatan produksi Samiler sebagai upaya untuk meningkatan mutu produksi dan pemasaran digital industri rumahan kerupuk Sameiler di Desa Wonosunyo, Kecamatan Gempol, Kabupaten Pasuruan. Kegiatan edukasi dan pendampingan dilakukan melalui 3 tahapan yaitu perencanaan, pelaksanaan, dan evaluasi tindak lanjut. Pada kegiatan perencanaan, dilakukan analisis situasi dan potensi desa Wonosunyo dalam hal produksi kerupuk Samiler yang merupakan kuliner khas setempat. Pada tahap pelaksanaan dilakukan edukasi melalui seminar dan pendampingan mulai dari proses pembuatan produk, pengawasan mutu, dan pemasaran digital. Hasil kegiatan ini meliputi 1) adanya analisis situasi dan potensi desa Wonosunyo yaitu kuliner khas kerupuk Samiler, 2) edukasi dilakukan melalui sosialisasi materi rangkaian kegiatan produksi meliputi kualitas dan pemasaran dengan menggunakan media sosial Facebook, dan 3) adanya evaluasi tindak lanjut kegiatan selanjutnya antara lain penguatan laporan keuangan sehingga akan tercatat Laba Rugi dan Harta dan adanya alat produksi yang mampu mempercepat dan lebih higienis. Kegiatan pendampingan selanjutnya diarahkan pada kualitas produksi pada variasi bentuk dan rasa kerupuk Samiler serta memperluas jejaring pemasaran, misalnya Tik Tok Live, Istagram, dan sebagainya.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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