MétaCan
Menu
Back to cohort
Record W4382314112 · doi:10.37695/pkmcsr.v5i0.1576

KELAYAKAN PENGEMBANGAN PENGOLAHAN BANDENG PADA INDUSTRI KECIL DI KELURAHAN GEBANG KECAMATAN SIDOARJO

2022· article· id· W4382314112 on OpenAlexaff
Muharom Muharom, Siswadi Siswadi, Krisnadhi Hariyanto

Bibliographic record

VenueProsiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesMathematicsPhysicsArt

Abstract

fetched live from OpenAlex

Usaha bandeng Bapak Norbert memiliki potensi untuk dikembangkan sehingga tidak hanya dijual dalam keadaan segar tetapi juga diolah menjadi produk lain yang memiliki nilai tambah. Abmas ini bertujuan untuk menganalisis prospek pengembangan pengolahan bandeng di Kelurahan Gebang, Kecamatan Sidoarjo. Metode pengambilan dilakukan secara purposive sampling. Analisis nilai ekonomi digunakan untuk memperkirakan nilai ekonomi total dari usaha pengolahan bandeng presto yang akan diolah dengan alat tepat guna. Alat tepat guna bandeng presto tersebut digunakan untuk mengetahui apakah jenis usaha pengolahan bandeng presto bisa berproduksi secara maksimal dengan citra rasa yang khas. Hasil abmas ini menunjukkan bahwa produk bandeng yang berkembang di Kelurahan Gebang, Kecamatan Sidoarjo yaitu bandeng presto / bandeng tanpa duri. Analisis kelayakan dilakukan untuk menunjukkan bahwa usaha pengolahan bandeng di Kelurahan Gebang, Kecamatan Sidoarjo layak untuk dikembangkan. Hal ini menunjukkan nilai produksi bandeng presto yang dihasilkan dengan alat tepat guna meningkat 30% dari produksi sebelumnya. Strategi pengembangan usaha pengolahan bandeng presto menjadi prioritas pada modalitas dan kriteria pemasaran. Peningkatan kualitas sumber daya manusia dan pengembangan saluran distribusi menjadi strategi prioritas dalam pengembangan usaha pengolahan bandeng di Kelurahan Gebang, Kecamatan Sidoarjo.
 
 
 Kata Kunci : Alat Tepat Guna, Ikan Bandeng, Kriteria Pemasaran, Nilai Tambah

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)0.017
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.011
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.006
Science and technology studies0.0170.002
Scholarly communication0.0030.003
Open science0.0040.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.286
Teacher spread0.205 · 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 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProsiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR)Same topicSMEs Development and Digital MarketingFrench-language works237,207