Kajian Infrastruktur Drainase terhadap Permasalahan Banjir di Kawasan Cibaduyut, Kecamatan Bojongloa Kidul, Kota Bandung
Bibliographic record
Abstract
Abstract. Bandung City, as one of the largest cities in Indonesia, faces recurring flooding problems, particularly in the Cibaduyut area, which is a priority flood-prone area. This study aims to identify the condition of the drainage network that causes flooding in the Cibaduyut area. Data collection methods were conducted through questionnaires, field observations, literature studies, and institutional surveys. The analytical methods used were flood discharge analysis and hydraulic analysis, which were used to describe the planned flood discharge and flow velocity. The variables studied included topography and slope, rainfall, and channel conditions. The results showed that the existing drainage system had a low capacity, only able to accommodate approximately 30% of the planned flood discharge of 3.22 m³/s. Meanwhile, channel capacity analysis showed a mismatch between the needs and the channel's capacity to accommodate runoff. Through channel redesign planning with increased dimensions, the flow capacity increased to 3.8 m³/s and was able to optimally accommodate the planned flood discharge. Abstrak. Kota Bandung sebagai salah satu kota terbesar di Indonesia menghadapi permasalahan banjir berulang, khususnya di Kawasan Cibaduyut yang merupakan salah satu titik rawan banjir prioritas. Penelitian ini bertujuan mengidentifikasi kondisi jaringan drainase yang menjadi penyebab banjir di Kawasan Cibaduyut. Metode pengumpulan data dilakukan melalui kuesioner, observasi lapangan, studi literatur, dan survei institusional. Metode analisis yang digunakan ialah analisis analisis debit banjir dan analisis hidrolik yang digunakan untuk menggambarkan debit banjir rencana dan kecepatan aliran. Variabel yang dikaji meliputi topografi dan kemiringan, curah hujan, dan kondisi saluran. Hasil penelitian menunjukkan bahwa sistem drainase eksisting memiliki kapasitas yang rendah, hanya mampu menampung sekitar 30% dari debit banjir rencana sebesar 3,22 m³/detik. Sementara itu, analisis kapasitas saluran menunjukkan ketidaksesuaian antara kebutuhan dan kemampuan saluran dalam menampung limpasan. Melalui perencanaan desain ulang saluran dengan peningkatan dimensi, kapasitas aliran meningkat menjadi 3,8 m³/detik dan mampu mengakomodasi debit banjir rencana secara optimal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".