Kearifan Lokal Masyarakat Dalam Upaya Pengelolaan Sumberdaya Air Desa Lerep,Kecamatan Ungaran Barat, Kabupaten Semarang
Bibliographic record
Abstract
ABSTRACTLerep Village, West Ungaran District, Semarang Regency is located not far from the of Ungaran City, it has the potential of agriculture, plantations and tourist villages. In addition to this potential, Lerep Village has a local wisdom practiced by the community for generations. The Iriban tradition is one of the local wisdoms aimed at managing water resources in Lerep Village. This study aims to find forms of local wisdom in efforts to manage water resources. The research method used is to use qualitative methods with a rationalistic approach. The rationalistic approach emphasizes reason in an analysis process. The conclusion of this research is form of local wisdom Iriban is a community effort in managing water resources for community life both for household and agricultural interests.Keywords: wisdom, local, management, water resources. ABSTRAK Desa Lerep, Kecamatan Ungaran Barat, Kabupaten Semarang letaknya tidak jauh dari pusat kota Ungaran, memiliki potensi pertanian, perkebunan dan desa wisata. Selain potensi tersebut, Desa Lerep memiliki kearifan lokal yang dilakukan masyarakat secara turun temurun. Tradisi Iriban merupakan salah satu kearifan lokal yang bertujuan dalam pengelolaan sumberdaya air di Desa Lerep. Penelitian ini bertujuan menemukan bentuk kearifan lokal dalam upaya pengelolaan sumberdaya air. Metode penelitian yang digunakan adalah menggunakan metode kualitatif dengan pendekatan rasionalistik. Pendekatan rasionaltistik menekankan akal dalam suatu proses analisis. Kesimpulan dari penelitian ini adalah bentuk kearifan lokal Iriban merupakan upaya masyarakat dalam mengelola sumberdaya air bagi kehidupan masyarakat baik untuk kepentingan rumah tangga,maupun pertanian.Kata kunci : kearifan, lokal, pengelolaan, sumberdaya air.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".