Analisis Penentuan Jalur Evakuasi Bencana Tanah Longsor pada Kawasan Permukiman
Bibliographic record
Abstract
ENGLISHIndonesia is an archipelagic country located on the equator. This causes rainfall in Indonesia to be quite high, around 2.898mm/year. Sukorejo Subdistrict, especially Bringinsari Village, which is located on the slopes of Mount Prau, has a high level of slope and rain intensity. With the high intensity of rain and changing weather conditions in Indonesia, Indonesia is an area prone to hydrometeorological disasters. Landslides are one of the hydrometeorological disasters. Landslides usually occur in areas with a high slope and have a high intensity of rain. The potential for landslide disasters in Bringinsari Village, especially in residential areas, makes disaster mitigation efforts something to pay attention to. Currently, there are no pre-disaster mitigation efforts, especially evacuation routes in Bringinsari Village, because mitigation efforts are only carried out when disasters occur and after disasters occur. Based on the analysis that has been carried out, six settlement points are prone to landslides and five evacuation points are located in Sumenet, Sumilir, Plalar, Gandring, and Balong. This evacuation point is in an open location in the form of a football field in each of these hamlets. The vulnerable points and evacuation points are connected with pre-disaster evacuation routes as a pre-disaster mitigation effort. INDONESIAIndonesia adalah negara kepulauan yang berada pada garis khatulistiwa, hal ini menyebabkan curah hujan di Indonesia cukup tinggi sekitar 2.898 mm/tahun. Kecamatan Sukorejo, khususnya Desa Bringinsari yang berada di lereng Gunung Prau memiliki tingkat kemiringan lereng dan intensitas hujan tinggi. Tingginya intensitas hujan dan kondisi cuaca di Indonesia yang berubah-ubah membuat Indonesia menjadi wilayah yang rawan mengalami bencana hidrometeorologi. Tanah longsor adalah salah satu bencana hidrometeorologi. Tanah longsor biasanya terjadi pada kawasan dengan kemiringan lereng yang tinggi dan memiliki intensitas hujan yang tinggi. Potensi bencana tanah longsor di Desa Bringinsari khususnya pada kawasan permukiman menjadikan upaya mitigasi bencana menjadi sesuatu yang diperhatikan. Saat ini, belum terdapat upaya mitigasi pra bencana khususnya jalur evakuasi di Desa Bringinsari karena upaya mitigasi hanya dilakukan saat bencana terjadi dan setelah bencana terjadi. Berdasarkan analisis yang telah dilakukan dihasilkan 6 (enam) titik permukiman rawan bencana longsor dan 5 (lima) titik evakuasi yang berlokasi pada Dusun Sumenet, Dusun Sumilir, Dusun Plalar, Dusun Gandring, dan Dusun Balong. Titik evakuasi ini berada pada lokasi terbuka berupa lapangan sepakbola di setiap masing-masing dusun tersebut. Titik rawan dan titik evakuasi tersebut dihubungkan dengan jalur evakuasi yang telah ditentukan sebagai upaya mitigasi prabencana.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".