Pemberdayaan UMKM Melalui Fasilitas Legalitas Usaha di Desa Bajing, Kroya: Implementasi Program Pendampingan NIB, P-IRT, dan Sertifikat Halal
Bibliographic record
Abstract
Kebijakan formalisasi Usaha Mikro, Kecil, dan Menengah (UMKM) melalui platform digital nasional menghadapi paradoks implementasi di tingkat perdesaan, di mana keterbatasan literasi digital menjadi penghalang utama. Tujuan program adalah meningkatkan kesadaran UMKM mengenai pentingnya Nomor Induk Berusaha (NIB), Pangan Industri Rumah Tangga (P-IRT), dan Sertifikasi Halal, serta memberikan pendampingan teknis langsung dalam proses pendaftarannya. Metode yang digunakan adalah penyuluhan partisipatif yang dikombinasikan dengan pendampingan teknis intensif. Hasilnya, program ini berhasil memfasilitasi penerbitan NIB bagi 11 UMKM peserta dengan tingkat keberhasilan 100% dan menginisiasi proses pengurusan P-IRT serta Sertifikasi Halal. Keberhasilan ini menunjukkan bahwa model intervensi high-touch yang menempatkan mahasiswa sebagai "perangkat lunak manusia" (human middleware) merupakan strategi efektif untuk mengakselerasi adopsi kebijakan digital di tingkat akar rumput.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.010 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".