Analisis Dampak Perubahan Iklim Dan Urban Sprawl Kota Palembang Pada Tata Ruang Perkotaan Di Kawasan Perbatasan Kabupaten Banyuasin
Bibliographic record
Abstract
ABSTRAK Sistem perencanaan pembangunan perkotaan cenderung masih menilai unsur iklim sebagai elemen statis, dimana selama ini dianggap tidak ada interaksi timbal balik antara iklim dengan perubahan tata guna lahan atau peruntukan ruang. Data iklim lebih sering dipergunakan sebagai data pendukung pernyataan kesesuaian lahan untuk pengembangan fungsi sebuah kawasan saja, terutama untuk kawasan pertanian dan perikanan. Kenyataannya, bahwa perubahan tata guna lahan yang disebabkan fenomena Urban Sprawl akan sangat berimplikasi pada sistem iklim. Penelitian ini bertujuan memanfaatkan data perubahan iklim sebagai salah satu unsur penting dalam perencanaan. Tahap awal adalah menganalisis data unsur iklim yang terdiri dari aspek curah hujan, penyinaran matahari, kecepatan angin, kelembaban, tekanan udara dan suhu serta melakukan klaster dan klasifikasi iklim. Penelitian ini menggunakan metode Kerangka DPSIR (Driving Force, Pressure, State, Impact, Response) yang merupakan kerangka kausal untuk menggambarkan interaksi antara masyarakat dan lingkungan. Hasil analisis diharapkan dapat dijadikan bahan pertimbangan dalam pengambilan keputusan dan pembuatan kebijakan. Kata kunci: Tata Ruang, Perubahan Iklim, Urban Sprawl ABSTRACT The urban development planning system tends to still assess the climate element as a static element, where so far it has been considered that there is no reciprocal interaction between climate and changes in land use or spatial allocation. Climate data is more often used as supporting data for land suitability statements for the development of the function of an area only, especially for agricultural and fishery areas. The reality is that changes in land use caused by the Urban Sprawl phenomenon will have implications for the climate system. This study aims to utilize climate change data as an important element in planning. The initial stage is to analyze the climate element data which consists of aspects of rainfall, solar radiation, wind speed, humidity, air pressure and temperature as well as conducting climate clusters and classifications. This study uses the DPSIR (Driving Force, Pressure, State, Impact, Response) framework method which is a causal framework for describing interactions between society and the environment. The results of the analysis are expected to be used as material for consideration in decision making and policy making. Keywords: Spatial Planning, Climate Change, Urban Sprawl
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".