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Record W4381621751 · doi:10.31315/psb.v4i1.8898

Evaluasi Lereng Bekas Tambang Pasir dan Batu Berdasarkan Nilai Faktor Keamanan di Dusun Tawang, Desa Sidorejo, Kecamatan Kemalang, Kabupaten Klaten

2023· article· id· W4381621751 on OpenAlexaff
Basitha Septia Wibowo, Wisnu Aji Dwi Kristanto, Muammar Gomareuzzaman

Bibliographic record

VenueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI · 2023
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Dusun Tawang, Desa Sidorejo, Kecamatan Kemalang, Kabupaten Klaten merupakan salah satu lokasi kegiatan pertambangan pasir dan batuan yang sudah dimulai sejak 2006. Kegiatan tersebut meninggalkan lereng yang tidak diperbaiki sehingga memiliki ancaman gerakan massa tanah dan/atau batuan. Desa Sidorejo juga sudah ditetapkan sebagai daerah rawan longsor dengan potensi tinggi pada bulan Desember 2018 oleh Pusat Vulkanologi dan Mitigasi Bencana Geologi. Penelitian ini dilakukan dengan tujuan mengetahui dan mengevaluasi kondisi eksisting lereng tambang menggunakan nilai faktor keamanan pada lereng bekas tambang. Metode yang digunakan yaitu studi literatur, survei lapangan dan pemetaan fisik lingkungan, serta metode uji laboratorium. Teknik analisis data dilakukan dengan menggunakan Metode Spencer dan Metode Analisis Deskriptif untuk mengevaluasi lereng bekas tambang terhadap gerakan massa tanah dan/atau batuan. Hasil penelitian menunjukkan bahwa gerakan massa tanah/batuan yang ada berupa keruntuhan permukaan lereng. Nilai faktor keamanan lereng sebesar 0,603 pada lereng 1; 0,799 pada lereng 2; dan 0,341 pada lereng 3. Ketiga lereng termasuk ke dalam kategori lereng tidak stabil.Kata Kunci: Evaluasi, Gerakan massa, Lereng, Bekas Tambang, Faktor Keamanan

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.022
GPT teacher head0.243
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMISame topicGeotechnical and construction materials studiesFrench-language works237,207