Analisis Indeks Kinerja Sistem Irigasi Daerah Irigasi Sambeng Kecamatan Kasiman Kabupaten Bojonegoro
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menganalisis indeks kinerja sistem irigasi di Daerah Irigasi (DI) Sambeng, Kecamatan Kasiman, Kabupaten Bojonegoro, dengan menggunakan pendekatan Penilaian Aset dan Kinerja Sistem Irigasi (PAKSI). Data dikumpulkan melalui observasi lapangan, wawancara dengan petugas dan petani, serta dokumentasi teknis jaringan irigasi. Komponen yang dievaluasi meliputi prasarana fisik, produktivitas tanam, sarana penunjang, organisasi personalia, dokumentasi, dan peran organisasi petani pengguna air (P3A). Hasil analisis menunjukkan bahwa rata-rata indeks kinerja sistem irigasi sebesar 32,84%, yang termasuk dalam kategori “Kurang dan Perlu Perhatian”. Faktor utama penyebab rendahnya kinerja adalah kerusakan pada jaringan irigasi dan rendahnya partisipasi P3A/GP3A/IP3A dalam pengelolaan air. Berdasarkan hasil ini, direkomendasikan untuk segera melakukan perbaikan infrastruktur, meningkatkan sistem inventarisasi aset, memperkuat koordinasi antarinstansi, serta mengadakan pelatihan peningkatan kapasitas pengelola irigasi. Diharapkan langkah-langkah tersebut dapat memperbaiki sistem distribusi air dan mendukung ketahanan pangan secara berkelanjutan.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".