Identifikasi Implementasi Pembangunan Green City Berdasarkan Persepsi Masyarakat di Kecamatan Rancasari Kota Bandung
Bibliographic record
Abstract
Abstract. The 20th century was characterized by rapid and often uncontrolled urban growth that led to population density that continued to increase every year, resulting in many problems in the city, for example land conversion, flooding, and congestion. The Green City concept is a city concept that partly implements programs to balance the ecosystem and improve environmental quality. The purpose of this research is to determine the extent of development performance and community interests for Green City development based on community perceptions in Rancasari District, Bandung City. The target is to identify the performance of Green City development in Rancasari District, Bandung City. The benefits of the results of this study are that it can be an evaluation and recommendation in an effort to improve local government performance with the development of the Green City concept. The approach method in this research is quantitative method by using Importance Performance Analysis (IPA) analysis method and qualitative descriptive analysis. Importance Performance Analysis (IPA) analysis is an analytical technique to identify the main performance factors that must be demonstrated by the organization to prioritize public satisfaction In the IPA analysis that has been carried out there are quadrants in determining the priority scale, namely Quadrant I (Concentrate these) which amounts to 5, Quadrant II (Keep up the good work) which amounts to 8 attributes, then Quadrant III (Low priority) amounts to 9, and Quadrant IV (Possible overkill) amounts to only 2 attributes. Based on the results of measuring the level of conformity of the Rancasari sub-district, the average is 54.75%. This percentage shows a poor level of conformity so that people are not satisfied with the government's performance in Green City Development. Abstrak. Abad ke-20 ditandai dengan pertumbuhan kota yang cepat dan seringkali tidak terkendali sehingga menimbulkan kepadatan penduduk yang terus meningkat setiap tahun nya mengakibatkan banyak nya permasalahan di kota, contoh alih fungsi lahan, banjir, serta kemacetan. Konsep Green City (Kota Hijau) adalah konsep kota yang sebagian menerapkan program untuk menyeimbangkan ekosistem dan meningkatkan kualitas lingkungan. Tujuan dilakukanya penelitian ini yaitu untuk mengetahui sejauh mana kinerja pembangunan dan kepentingan masyarakat untuk pembangunan Green City berdasarkan persepsi masyarakat di Kecamatan Rancasari Kota Bandung. Sasarannya adalah teridentifikasinya kinerja pembangunan Green City di Kecamatan Rancasari Kota Bandung. Adapun manfaat dari hasil penelitian ini yaitu dapat menjadi evaluasi dan rekomendasi dalam upaya peningkatan kinerja pemerintah daerah dengan pembangunan konsep Green City. Metode pendekatan dalam penelitian ini yaitu metode kuantitatif dengan menggunakan metode analisis Importance Performance Analysis (IPA). Analisis Importance Performance Analysis (IPA) adalah teknik analisis untuk mengidentifikasi faktor kinerja utama yang harus ditunjukkan oleh organisasi untuk memprioritaskan kepuasan masyarakat Dalam Analisa IPA yang telah dilakukan terdapat kuadran dalam penentuan skala prioritas, yaitu Kuadran I (Concentrate these) yang berjumlah 5, Kuadan II (Keep up the good work) yang berjumlah 8 atribut, lalu Kuadran III (Low priority) berjumlah 9, dan Kuadran IV (Possible overkill) berjumlah yang hanya 2 atribut. Berdasarkan hasil pengukuran tingkat kesesuaian kecamatan Rancasari rata-rata sebesar 54,75%. Persentase ini menunjukkan tingkat kesesuaian yang kurang baik sehingga masyarakat tidak puas dengan kinerja pemerintah dalam Pembangunan Green City.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".