Pendekatan Tata Ruang dalam Pengendalian Daerah Sempadan Sungai sebagai Area Resapan Banjir di Desa Beleka Lombok Tengah
Bibliographic record
Abstract
Beleka Village, located in Central Lombok Regency, is an area with a high vulnerability to flood disasters, particularly around the riverbank buffer zones. This issue is exacerbated by land-use changes and the low public awareness of the importance of maintaining the ecological function of riverbank areas as water infiltration zones. This community service activity aims to educate the public and provide adaptive and sustainable spatial planning recommendations as part of flood control efforts. The approach used is participatory, involving outreach activities, participatory mapping, and focus group discussions (FGDs) with residents, community leaders, and village government officials. The results of the activity show that spatial planning approaches can improve community understanding of the strategic function of riverbanks and encourage the formation of local agreements to protect and rehabilitate these areas as conservation and flood infiltration zones. In addition, a draft spatial utilization plan was produced, based on disaster mitigation principles that integrate local wisdom and ecological aspects. This activity highlights the importance of synergy between scientific approaches and community participation in sustainable spatial management at the village level. It is hoped that this initiative can serve as a replicable model for other villages facing similar challenges, particularly in the context of flood control through spatial planning.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".