Analisis Efisiensi Rantai Pasok Bawang Merah Di Kabupaten Bantul
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bawang merah (Allium ascalonicum) sebagai salah satu komoditas unggulan Kabupaten Bantul yang memberikan kontribusi cukup tinggi terhadap perkembangan ekonomi. Tujuan dari penelitian ini adalah menganalisis kondisi rantai pasok bawang merah dan menyusun alternatif skenario sistem manajemen rantai pasok bawang merah di Kabupaten Bantul. Penelitian berlangsung pada bulan April – Juli 2019. Penelitian menggunakan analisis deskriptif, evaluasi dengan membandingkan aktivitas anggota rantai pasok dengan menggunakan analisis marjin pemasaran, farmer’s share serta analisis AHP. Teknik pengambilan sampel yang digunakan dalam penelitian ini adalah snowball sampling, sejumlah 50 petani dan 10 pedagang. Hasil penelitian menunjukan bahwa terdapat 3 saluran rantai pasok bawang merah di Kabupaten Bantul, saluran I (petani-pedagang besar lokal-pengecer lokal-konsumen), saluran II (petani-pedagang pengumpul-pedagang besar lokal-pengecer lokal-konsumen), saluran III (petani-pedagang pengumpul-pedagang besar non lokal-pengecer non lokal-konsumen). Berdasarkan analisis AHP, dalam membentuk manajemen rantai pasokan bawang merah yang efisien, kriteria meningkatkan kemitraan atau bekerjasama semua pihak menjadi prioritas yang paling berperan penting.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it