Bibliographic record
Abstract
Banjir dan Bekasi sudah menjadi dua hal yang hampir mustahil dipisahkan. Sejarah mencatat banjir sudah terjadi di Bekasi sejak masa Kerajaan Tarumanegara pada abad ke-5 Masehi yang dituliskan dalam Prasasti Tugu. Pada masa kolonial, banjir di Bekasi selalu melanda setiap musim penghujan tiba. Kondisi ini terus berlanjut hingga pasca Reformasi, bahkan saat ini. Seringnya banjir melanda Bekasi membuat pemerintah yang berkuasa saat itu harus menemukan cara untuk melakukan penanggulangan banjir yang melanda. Tulisan ini berusaha mendeskripsikan sejarah banjir sejak masa kolonial dan mengetahui bagaimana upaya pemerintah Bekasi dalam menangani permasalahan banjir yang sering terjadi. Penulisan artikel ini menggunakan metode sejarah dengan melakukan pembacaan mendalam berbagai sumber, seperti koran, foto, artikel dan buku. Hasil penelitian menunjukan jika banjir yang terjadi di Bekasi disebabkan oleh tingginya curah hujan, terjadinya alih fungsi lahan secara berlebihan serta ketidakmampuan pemerintah dalam melakukan pengelolaan sumber daya air. Selain itu mitigasi banjir yang dilakukan pemerintah dari masa kolonial hingga masa reformasi masih kurang maksimal. Terbukti dari banjir yang tetap terjadi hingga kini dengan intensitas yang lebih sering. Floods and Bekasi have become two things that are almost impossible to separate. History records that flooding has occurred in Bekasi since the time of the Tarumanegara Kingdom in the 5th century AD which was written in the Tugu Inscription. In colonial times, floods in Bekasi always hit every rainy season. This condition has continued until after the Reformation, even today. The frequent floods that hit Bekasi forced the government in power at that time to find a way to deal with the floods that hit. This paper attempts to describe the history of flooding since the colonial period and to find out how the Bekasi government's efforts to deal with frequent flooding problems. The writing of this article uses the historical method by doing in-depth reading of various sources, such as newspapers, photographs, articles and books. The results of the study show that the flooding that occurred in Bekasi was caused by high rainfall, excessive land conversion and the government's inability to manage water resources. In addition, flood mitigation carried out by the government from the colonial period to the reformation period was still not optimal. This is evidenced by the floods that have continued to occur to this day with more frequent intensity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".