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Record W2989738109 · doi:10.36805/bi.v2i2.419

PENGEMBANGAN EKONOMI KREATIF UNTUK MENINGKATKAN PENDAPATAN MASYARAKAT DESA TANJUNGPAKIS KECAMATAN PAKISJAYA KABUPATEN KARAWANG

2018· article· id· W2989738109 on OpenAlexaff
Budi Rismayadi

Bibliographic record

VenueBUANA ILMU · 2018
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

ABSTRAK Peranan penting adanya penyuluhan terhadap upaya meningkatkan keahlian masyarakat petani dan nelayan di pedesaan merupakan tujuan yang ingin dicapai. Melalui penyuluhan masyarakat mendapatkan informasi dan wawasan, sehingga masyarakat dapat memahami secara mendalam tentang ekonomi kreatif serta manfaatnya bagi peningkatan pendapatannya. Materi penyuluhan yang disampaikan disesuaikan dengan potensi sumberdaya yang ada di desa. Materi penyuluhannya antara lain pemahaman mengenai apa yang dimaksud dengan ekonomi kreatif dan definisinya, mencakup apa itu kreatifitas, bagaimana memanfaatkan bahan baku local yang dapat di proses menjadi produk, proses pengolahan tempurung kelapa menjadi produk hiasan, produk-produk olahan dari udang dan ikan menjadi terasi, teknik pengemasan dan pemasaran terasi, mengingat desa Tanjungpakis sudah terkenal sebagai produsen terasi jembret yang cukup dikenal oleh warga Karawang. Kegiatan penyuluhan untuk penguatan ekonomi kreatif berbasis sumberdaya desa dapat memberikan manfaat yang besar bagi masyarakat. Hal ini terlihat dari antusiasnya masyarakat dalam mengikuti kegiatan penyuluhan dan dari tanya jawab juga tampak bahwa masyarakat merasa termotivasi untuk mengembangkan kreatifitas usahanya, demikian juga masyarakat yang hanya mengandalkan pekerjaannya sebagai petani dan nelayan tampaknya cukup tertarik untuk mencoba memulai mengembankan usaha kreatifitasnya Kata Kunci : Penyuluhan, Sumberdaya, Ekonomi Kreatif

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1150.035

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 head0.290
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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