Penentuan Prioritas Lokasi Penambahan Ruang Terbuka Hijau sebagai Upaya dalam Mengurangi Efek Urban Heat Island di Kabupaten Lumajang
Bibliographic record
Abstract
Abstract. The Urban Heat Island (UHI) phenomenon refers to increased air temperatures in urban areas resulting from high building density and the reduction of green open spaces (GOS). Uncontrolled land-use conversion is a major contributor to this phenomenon, which has also been observed in Lumajang Regency in recent years. This study aims to estimate the required additional GOS and identify potential locations for its development as a UHI mitigation strategy. A quantitative approach was applied using secondary data obtained from relevant government institutions. Data were analyzed through spatial analysis techniques, including the calculation of GOS requirements based on Law Number 26 of 2007. The findings indicate that Lumajang Regency requires an additional 28.55 hectares of GOS. Site selection for GOS development was based on several parameters, including the Thermal Humidity Index (THI), Normalized Difference Vegetation Index (NDVI), slope gradient, and proximity to residential areas. Overall, 134.93 hectares of land were identified as potentially suitable for GOS development. These results provide a policy reference for local government planning to mitigate UHI impacts. Abstrak. Fenomena Urban Heat Island (UHI) merupakan peningkatan suhu udara di kawasan perkotaan akibat kepadatan bangunan dan berkurangnya ruang terbuka hijau (RTH). Alih fungsi lahan menjadi salah satu penyebab utama meningkatnya fenomena ini, yang juga terjadi di Kabupaten Lumajang dalam beberapa tahun terakhir. Penelitian ini bertujuan untuk menghitung kebutuhan penambahan RTH serta mengidentifikasi lokasi potensial pengembangannya sebagai upaya mitigasi UHI. Pendekatan yang digunakan adalah kuantitatif dengan memanfaatkan data sekunder yang diperoleh dari instansi pemerintah terkait. Analisis data dilakukan menggunakan teknik analisis spasial, termasuk perhitungan kebutuhan RTH berdasarkan Undang-Undang Nomor 26 Tahun 2007. Hasil penelitian menunjukkan bahwa Kabupaten Lumajang masih memerlukan tambahan RTH seluas 28,55 hektare. Penentuan lokasi RTH mempertimbangkan beberapa faktor, yaitu Thermal Humidity Index (THI), Normalized Difference Vegetation Index (NDVI), kemiringan lereng, dan jarak dari permukiman. Secara keseluruhan, tersedia lahan potensial seluas 134,93 hektare untuk pengembangan RTH. Temuan ini menjadi dasar rekomendasi kebijakan bagi Pemerintah Kabupaten Lumajang dalam perencanaan pengembangan RTH guna mengurangi dampak UHI.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".