Manajemen Taman Milik Pemerintah Kota Bandung Berbasiskan Pendekatan Manajemen Aset
Bibliographic record
Abstract
Abstrak. Manajemen aset merupakan pendekatan yang awalnya diterapkan oleh sektor privat dan terbukti menghasilkan keuntungan yang signifikan, sehingga mulai diadopsi oleh pemerintah untuk mengelola aset-aset publik. Penerapan manajemen aset di sektor publik lebih banyak pada pengelolaan infrastruktur seperti jaringan jalan (roads), rel kereta api (railroads), drainase (drainage), gorong-gorong (culverts), jaringan listrik (electricity), dan mulai meluas ke aset real property seperti lahan (lands) dan bangunan (buildings). Salah satu aset penting perkotaan adalah taman. Taman sebagai salah satu bagian dari Ruang Terbuka Hijau (RTH) memiliki peran dan manfaat yang besar bagi masyarakat perkotaan. Namun, kebanyakan manfaat taman sifatnya berorientasi jangka panjang dan tidak secara langsung memberikan keuntungan ekonomi yang besar seperti halnya mall, permukiman, pertokoan, dan fasilitas sosial lainnya. Akibatnya, seringkali keberadaan taman dikesampingkan. Beragam persoalan taman terkait kuantitas dan kualitas kerap dijumpai di kota-kota besar di Indonesia, salah satunya Kota Bandung. Untuk mengatasi persoalan-persoalan tersebut, pengelolaan taman dapat dilakukan dengan menerapkan konsep manajemen aset. Penelitian ini bertujuan untuk menerapkan model pendekatan manajemen aset terhadap taman berbasiskan Sistem Informasi Geografis (SIG) dalam rangka mengoptimalkan fungsi taman. Penelitian ini menggunakan metodologi deskriptif melalui teknik wawancara dengan pihak-pihak terkait pengelolaan taman dan observasi lapangan pada taman-taman yang ada di wilayah penelitian.Abstract. Asset management is an approach that initially was applied by private sector and had been proven to generate significant benefits to the corporate. Therefore, this concept was adopted by government to manage public assets. The implementation of asset management in public sectors tends to be applied for infrastructure management such as roads, railroads, drainage, culverts, electricity, and starting to expand for real property assets such as lands and buildings. One of many important city assets is park. Park as a part of green space has been playing a great role and giving so much benefit for the citizen. Unfortunately, most of the benefits of parks are long-term oriented and do not instantly provide great economic benefits as mall, housing, shopping center, and other social facilities do. Consequently, the presence of park is being neglected often. Various issues related to quantity and quality of park is found in big cities in Indonesia, such as Bandung City. In order to resolve these issues, park management could be conducted by implementing asset management concept. This research aims to apply asset management approach to the park, based on Geographic Information System (GIS) in order to optimize the function of the park. This study used a descriptive methodology through technical interviews with relevant parties and field observations at existing parks in the area of research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.091 | 0.025 |
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".