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Record W4400390534 · doi:10.33369/jkf.6.2.75-82

ANALISIS ZONA RAWAN GEMPA BUMI DI KABUPATEN BENGKULU SELATAN BERDASARKAN PERCEPATAN TANAH PUNCAK MENGGUNAKAN FORMULA KANAI

2023· article· id· W4400390534 on OpenAlexaff
Giltro Kencoro, M Farid, Arif Ismul Hadi, Darmawan Ikhlas Fadli, Agung Sedayu

Bibliographic record

VenueJurnal Kumparan Fisika · 2023
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsSeismologyHumanitiesGeologyArt

Abstract

fetched live from OpenAlex

ABSTRAK Provinsi Bengkulu terletak di antara Sumatra Fault Zone dan Mentawai Fault Zone, yang mana merupakan sistem patahan paling berbahaya di Pulau Sumatera, Indonesia. Selain itu, gempa bumi Bengkulu tahun 2000 dengan magnitudo sebesar Mw 7,9 menyebabkan banyak korban jiwa dan harta benda di sekitar wilayah studi, dan banyak gempa lain yang merusak yang terjadi setelah gempa ini. Penentuan zona rawan gempa Kabupaten Bengkulu Selatan penting dilakukan untuk mengurangi kerusakan akibat gempa. Oleh karena itu, perekaman data mikrotremor short period dilakukan di 65 titik di daerah penelitian. Analisis data ambient noise dapat membantu mengidentifikasi local site-efect di Kabupaten Bengkulu Selatan dengan menggunakan metode Horizontal to Vertical Spectral Ratio (HVSR). Frekuensi fundamental alami berkisar antara 1.0 Hz hingga 9.3 ​​Hz, dan faktor amplifikasi berkisar antara 1.8 hingga 4.4. Nilai PGA diperoleh dari kejadian gempa bumi selama 100 tahun dan dihitung menggunakan persamaan Kanai. Hasil menunjukkan bahwa nilai PGA berkisar antara 0.18 g hingga 0.78 g. Zona rawan gempa di Kabupaten Bengkulu Selatan terbagi menjadi tiga zona, yaitu zona klasifikasi rendah (Kota Manna, Pasar Manna, Bunga mas, dan Seginim) , sedang (Pino Raya, Air Nipis, dan Ulu Manna), dan tinggi (Manna, Kedurang, dan Kedurang Ilir). Hasil penelitian ini dapat menjadi rekomendasi bagi pemangku kepentingan untuk mempertimbangkan langkah-langkah yang tepat untuk desain dan konstruksi tahan gempa di Kabupaten Bengkulu Selatan. Kata kunci: Gempa Bumi, HVSR, Kabupaten Bengkulu Selatan, PGA. ABSTRACT Bengkulu Province is between the Sumatra Fault Zone and the Mentawai Fault Zone, the most dangerous fault system in Sumatra, Indonesia. In addition, the 2000 Bengkulu earthquake with a magnitude of Mw 7.9 caused a significant loss of life and property in the study area, and many other destructive earthquakes occurred after this earthquake. Determining the earthquake-prone zone of South Bengkulu Regency is essential to reducing earthquake damage. Therefore, short-period microtremor data recording was conducted at 65 points in the study area. Analysis of ambient noise data can help identify local site effects in South Bengkulu Regency using the Horizontal to Vertical Spectral Ratio (HVSR) method. The natural fundamental frequency ranges from 1.0 Hz to 9.3 Hz, and the amplification factor ranges from 1.8 to 4.4. PGA values were obtained from a 100-year earthquake event and calculated using the Kanai equation. The results show that PGA values range from 0.18 g to 0.78 g. The earthquake-prone zones in South Bengkulu Regency are divided into three zones: low (Kota Manna, Pasar Manna, Bunga Mas, and Seginim), medium (Pino Raya, Air Nipis, and Ulu Manna), and high (Manna, Kedurang, and Kedurang Ilir). The results of this study can serve as recommendations for stakeholders to consider appropriate measures for earthquake-resistant design and construction in South Bengkulu Regency. Keywords: Earthquake, HVSR, South Bengkulu Regency, PGA.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.030
GPT teacher head0.240
Teacher spread0.210 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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