Identifikasi Pengembangan Ruang Terbuka Hijau
Bibliographic record
Abstract
Abstract. The city of Cirebon is one of the cities in West Java that is experiencing rapid development, accompanied by an increase in the rate of population growth each year by 2,91% per year. This rapid development has led to changes in land use where vegetation land is turned into built-up land, it is stated that almost ± 55% of the area in Cirebon City is built-up land. Meanwhile, the amount of land designated as public green open space is still 10,5% less than the 20% should be, while for private green open space the amount is 10%. Therefore, it is necessary to identify the development of Green Open Spaces in Cirebon City. The approach method used is using remote sensing techniques to identify the development of green open space in the city of Cirebon using Landsat 8 Imagery by paying attention to 3 aspects, namely biological, physique and social aspects. The variables used are vegetation density or NDVI, comfort index or THI and population density. The data used are Landsat 8 imagery, population, climatology and land use. The purpose of this study was to determine the location and extent of green open space development in the city of Cirebon. The results of this study are Cirebon City is dominated by a very dense vegetation density level of 1.826,17 Ha, the comfort index is 4,49% uncomfortable conditions, 86,71% less comfortable and 8,80% comfortable from the area of Cirebon City, dominated by The population density level is very dense at 82,67% of the area of Cirebon City. Based on the results of overlapping maps of the three variables, namely NDVI, THI and population density, there are 2 zones of green open space development including the highly prioritized zone of 159,14 Ha and the prioritized zone of 2.587,82 Ha.
 Abstrak. Kota Cirebon termasuk kota di Jawa Barat yang mengalami pembangunan yang pesat, dibarengi pula oleh meningkatnya laju pertumbuhan penduduk tiap tahunnya sebesar 2,91% pertahun. Pembangunan yang pesat ini menimbulkan terjadinya perubahan guna lahan yang dimana lahan vegetasi berubah menjadi lahan terbangun, disebutkan bahwa hampir ± 55% wilayah di Kota Cirebon merupakan lahan terbangun. Sedangkan lahan yang diperuntukkan sebagai Ruang Terbuka Hijau publik jumlahnya masih kurang sebesar 10,5 % dari yang seharusnya 20%, sedangkan untuk Ruang Terbuka Hijau privat jumlahnya sudah memenuhi yakni 10%. Oleh karena itu, diperlukan adanya identifikasi pengembangan Ruang Terbuka Hijau di Kota Cirebon. Metode pendekatan yang digunakan adalah menggunakan teknik penginderaan jauh untuk mengidentifikasi pengembangan RTH di Kota Cirebon menggunakan Citra Landsat 8 dengan memperhatikan 3 aspek yakni aspek biologi, fisik dan sosial. Variabel yang digunakan adalah kerapatan vegetasi atau NDVI, indeks kenyamanan atau THI dan kepadatan penduduk. Data yang digunakan adalah Citra Landsat 8, jumlah penduduk, klimatologi dan penggunaan lahan. Tujuan dari penelitian ini adalah mengetahui lokasi dan luasan pengembangan RTH di Kota Cirebon. Hasil dari penelitian ini adalah Kota Cirebon didominasi oleh tingkat kerapatan vegetasi sangat rapat sebesar 1.826,2 Ha, indeks kenyamanan didapatkan kondisi tidak nyaman 4,49%, kurang nyaman 86,7% dan nyaman 8,8% dari luas Kota Cirebon, didominasi oleh tingkat kepadatan penduduk sangat padat sebesar 82,7% dari luas Kota Cirebon. Berdasarkan hasil tumpang tindih peta ketiga variabel yakni NDVI, THI dan kepadatan penduduk didapatkan 2 zona pengembangan RTH diantaranya adalah zona sangat diprioritaskan sebesar 159,1 Ha dan zona diprioritaskan sebesar 2.587,8 Ha.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".