Analisis Ketersediaan Ruang Terbuka Hijau Menggunakan Pendekatan Indeks Hijau-Biru Indonesia Di Kelurahan Tamalanrea
Bibliographic record
Abstract
Abstract. The purpose of this study is to determine the availability of green open space in Tamalanrea Village and how the strategy to maximize green open space in Tamalanrea Village and can be an input or reference for the government as a policy determinant in development, private parties, social institutions, or communities that act as development implementation and for planners in terms of increasing development, especially in terms of providing green open space. This research is qualitative research with data collection techniques using observation, interview, documentation and literature study methods. The data obtained were then analyzed using spatial approach, qualitative descriptive analysis, and Indonesian Green-Blue Index (IHBI) approach. The conclusion of this study, is that the availability of green open space in Tamalanrea Village based on MINISTER OF ATR / BPN Number 14 of 2022 concerning the provision and utilization of green open space consisting of allotment areas or green open space zones, namely RT parks and green lanes, allotment areas or other zones, namely agricultural areas, green open spaces on plots, namely parcels in residential zones, parcels in office zones, and home yards, as well as blue open space areas, namely lakes whose availability needs to be maximized ecologically and socially based on MINISTER OF ATR / BPN Number 14 of 2022. Abstrak. Tujuan penelitian ini adalah untuk mengetahui ketersediaan ruang terbuka hijau di Kelurahan Tamalanrea dan bagaimana strategi memaksimalan ruang terbuka hijau di Kelurahan Tamalanrea serta dapat menjadi bahan masukan atau acuan bagi pemerintah sebagai penentu kebijakan dalam pembangunan, pihak swasta, lemabaga sosial, atau masyarakat yang bertindak sebagai pelaksanaan pembangunan dan bagi perencana dalam hal peningkatan pembangunan terutama dalam hal penyediaan ruang terbuka hijau. Penelitian ini adalah penelitian kualitatif dengan teknik pengumpulan data menggunakan metode observasi, wawancara, dokumentasi dan studi literatur. Data yang diperoleh selanjutnya dianalisis dengan pendekatan spasial, analisis deskriptif kualitatif, dan pendekatan Indeks Hijau-Biru Indonesia (IHBI). Kesimpulan dari penelitian ini, adalah bahwa ketersediaan ruang terbuka hijau di Kelurahan Tamalanrea berdasarkan PERMEN ATR/BPN Nomor 14 Tahun 2022 tentang penyediaan dan pemanfaatan ruang terbuka hijau yang terdiri dari kawasan peruntukan atau zona ruang terbuka hijau yaitu taman RT dan jalur hijau, kawasan peruntukan atau zona lainnya yaitu kawasan pertanian, ruang terbuka hijau pada kavling yaitu persil pada zona perumahan, persil pada zona perkantoran, dan pekarangan rumah, serta kawasan ruang terbuka biru yaitu danau yang ketersediaannya perlu dimaksimalkan secara ekologis dan sosial berdasarkan PERMEN ATR/BPN Nomor 14 Tahun 2022.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".