Hasil Pencarian  ::  Simpan CSV :: Kembali

"This study discusses the evaluation of Hara’s model to estimate seismic moment magnitude (MW) by using teleseismic waveform data, and then presents the development of an extended Hara model. Both models use the maximum amplitude of displacement and epicenter distance, as well as the duration of high-frequency energy radiation, of the vertical component of earthquake P-wave records. Nineteen moderate-magnitude (5.0 £ MW£ 7.0), shallow (depths £ 70 km), Sumatra subduction megathrust earthquake data sets recorded by the KAPI seismograph station (Kappang, South Sulawesi) in 2010 and 2011 were used in this study. The analysis is performed to obtain the maximum amplitude of displacement, epicenter distance, and the duration of high-frequency energy radiation on the first arriving P-wave. The main results show that Hara’s model (2007) overestimates MW to be less than 7.0 compared with that obtained from the Global Centroid Moment Tensor (CMT) catalog. The extended Hara model was developed with the use of the same basic equation, and the resulting coefficients are ? = 0.538792, ? = 0.783840, ? = 0.242616, and ? = 4.929095. The mean and standard deviation of the difference between the extended Hara model and the Global CMT catalog are 0.01 and 0.14, respectively."

"Penelitian ini berfokus pada pengembangan sistem peringatan dini gempa bumi yang memanfaatkan arsitektur event-driven dan model deep-learning. Tujuannya adalah untuk memodelkan data seismik guna mendeteksi gelombang awal, hiposenter, magnitudo, dan kedalaman gempa. Penulis mengumpulkan data dari ratusan titik seismograf dan mengolahnya dengan model deep-learning untuk menghasilkan prediksi yang akurat. Sistem ini dirancang untuk memberikan visualisasi dan informasi yang mendukung Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) dalam mendeteksi aspek-aspek kritis gempa. Selain itu, penulis mengembangkan sistem terdistribusi untuk mengelola permintaan dan pengolahan data skala besar dengan efisiensi tinggi. Antarmuka pemrograman aplikasi (API) juga disajikan untuk memungkinkan prediksi data yang mudah diakses dan dipahami. Terakhir, integrasi antara model machine learning dengan backend dan frontend dirancang untuk memberikan tampilan yang ramah pengguna. Penelitian ini berkontribusi dalam mengembangkan sistem peringatan dini gempa yang lebih canggih dan responsif, sehingga dapat meningkatkan kesiapan dan keamanan masyarakat dalam menghadapi bencana alam.

---

This study focuses on the development of an earthquake early warning system utilizing event-driven architecture and deep-learning models. The aim is to model seismic data to detect initial waves, hypocenters, magnitude, and depth of earthquakes. Data from hundreds of seismograph points were collected and processed using deep-learning models to generate accurate predictions. The system is designed to provide visualizations and information to support the Meteorology, Climatology, and Geophysics Agency (BMKG) in detecting critical earthquake aspects. Additionally, a distributed system was developed to manage large-scale data requests and processing efficiently. An Application Programming Interface (API) is also presented for accessible and understandable data predictions. Finally, the integration of machine learning models with backend and frontend is designed to offer a user-friendly display. This research contributes to the development of a more sophisticated and responsive early warning system, enhancing public preparedness and safety in the face of natural disasters."

"

Kota Palu sebagai bagian Provinsi Sulawesi Tengah secara tektonik berada dekat dengan sumber gempa aktif crustal, yaitu sesar segmen Sulawesi Tengah. Sesar tersebut terdiri dari banyak segmen, diantaranya yang sudah dikenal adalah Sesar Besar Palu-Koro memanjang dari utara ke selatan. Di ujung selatan terhubung sesar Matano dan di utara terhubung dengan subduksi Utara Sulawesi (North Sulawesi Subduction) dan Selat Makasar bagian utara. Pembangunan infrastruktur berbasis mitigasi kegempaan di Indonesia merujuk Peraturan Bangunan Tahan Gempa berdasarkan Peta Bahaya Gempabumi SNI 1726 Tahun 2019. Kota Palu dan wilayah sekitar sesar segmen Sulawesi Tengah menjadi wilayah yang perlu dilakukan penelitian dengan mempertimbangkan efek kondisi site lokal. Parameter kondisi lokal meliputi jenis situs tanah, periode dominan tanah metode Horizontal to Vertical Spectral Ratio (HVSR) dan estimasi kedalaman bedrock menggunakan metoda Spatial Autocorrelation (SPAC) menjadi bagian parameter studi karakteristik ground motion di Kota Sulawesi Tengah. Penelitian ini menggunakan parameter gempa magnitudo gempa M_L 1,5-6,5. Pengolahan data ground motion menggunakan data hasil observasi sinyal 5 sensor Jaringan Strong motion Nasional BMKG sampling 100Hz, 5 sensor  jaringan strong motion terpasang sementara sampling 100Hz dan 25 sensor Jaringan Array Velocity Broadband dengan sampling 250 Hz. Jaringan khusus array ini hasil kerjasama BMKG dengan ANU (Australian National University) yang dipasang di sekitar Kota Palu dan dekat sesar segmen Sulawesi Tengah dalam durasi 3 bulan. Tujuan dalam studi ini adalah untuk mengkaji karakteristik dan pembangunan model ground motion segmen fault Sulawesi Tengah. Karakteristik ground motion model yang dibangun dikaji dari uji model regional dan lokal dengan katalog gempa utama (independent) dan gempa gabungan foreshock,mainshock dan aftershock (dependent). Hasilnya menunjukkan karakteristik ground motion hasil dependent mempunyai nilai hasil model yang lebih rendah dibandingan independent, fitting model regional menunjukkan hasil bervariasi tingkat kecocokannya terhadap data observasi masing-masing fault yaitu dengan melihat hasil garis korelasi terhadap data observasi dan hasil residualnya. Model tersebut diuji menggunakan data observasi gempa merusak 29 Mei 2017 Mw 6,6 dan gempa merusak 2018 magnitudo 7,4. Hasilnya menunjukkan model GMPE dependent mempunyai nilai estimasi GM-PGA model yang berada pada distribusi data observasi, sedangkan hasil model independent mempunyai tingkat kecocokan berada di atas sebaran data observasi. Sedangkan pengujian GMSA median M=3-4 dan M=4-5 model dependent dan independent terhadap dari data observasi M=3-4 dan M=4-5 di luar data pembangun model, menunjukkan hasil korelasi yang cukup baik terhadap dua model tersebut. Pemahaman kondisi site lokal menjadi sangat penting dan menjadi bagian dalam perhitungan GM-PGA dan dipertimbangkan dalam penentuan nilai estimasi tingkat goncangan dalam bagian desain infrastruktur mitigasi bencana gempa bumi.     

 

---

Palu City in one major city in Indonesia which has administratively is the part of Central Sulawesi Province. It has the potential to develop the big infrastructure which has to consider mitigation aspect, due to tectonically it has located close to earthquake active source, particularly segments crustal zone of Central Sulawesi. Central Sulawesi fault has the many faults segmentation, it is called The Active Major Fault System of Central Sulawesi, as well known Palu Koro Fault System zone. It was along the north to southward close to Palu Valley. Development of infrastructure with earthquake hazard mitigation accordance to SNI 1726:2019. Local site classification parameters using the dominant period HVSR (Horizontal Vertical Spectral Ratio), estimation deep of engineering bedrock using SPAC method (Spatial Auto Correlation) as well done. The understanding of the local seismic condition and seismotectonic mechanism based on seismicity data are significantly contributing to know earlier the possibility of the amplification, which have related PGA value with the distance. In this study used 5 National Strong motion Network Station of  BMKG in Palu, 25 Array Network Broadband Velocity Temporarily Station of BMKG-ANU and 5 Regional Strong motion Network Temporarily Station along the Palu-Koro fault and short period for the mini regional network. The purpose of this research to study the characteristics of the local ground motion GM-PGA model from multi fault in Central of Sulawesi, with considered the local site effect.  All these parameters contribute to play roles within the form of the GMPE model.The characteristics of ground motion in this research using independent (mainshock)-independent (foreshock, mainshock, aftershock) regional and local earthquake catalog. The result showed characteristics of ground motion dependent has the calculated value is lower than independent, and the regional model showed the fitting variated to micro fault observed data. It can be seen using correlated regression and residuals. Moreover, when compared with two devastating earthquakes, 29th May 2017 Mw 6.6 and Palu earthquake Mw 7.4 showed that the dependent model is fitted well with distribution of observed data, while for the independent model is overestimated. Meanwhile to calibrate GMSA has used Median GMSA for M=3-4 and M=4-5 to GMSA data observed of M=3-4 and M=4-5. The results showed that the well correlated between of Median GMSA to data observed distribution. The Understanding of local seismic is very important to asses the related PGA value with the distance in GM-PGA and GMSA in GMPE. The GMPE model could be used to be considered in detail engineering design process to determine the level of potential shaking when implement development mitigation based.    

"

"Gerakan tanah adalah proses ketika material tanah atau batuan mengalami perpindahan akibat gravitasi bumi dan dampaknya merugikan bagi lingkungan hingga menimbulkan korban jiwa (Noor, 2011). Berdasarkan catatan dari Badan Nasional Penanggulangan Bencana, terdapat 289 kejadian bencana akibat gerakan tanah terhitung tahun 2018 hingga tahun 2022 di Kabupaten Banyumas, Provinsi Jawa Tengah (Data Informasi Bencana Indonesia (DIBI)). Pergerakan tanah dipengaruhi oleh parameter-parameter yang berpengaruh terhadap gerakan tanah seperti litologi, aspek lereng, curvature, curah hujan, kemiringan lereng, elevasi, tata guna lahan, jarak dari sungai, jarak dari struktur, dan normalized difference vegetation index (NDVI) (Chen et al., 2021). Tujuan dari penelitian ini yaitu untuk mengidentifikasi daerah rawan pergerakan tanah berdasarkan parameter-parameter tersebut dan memetakan daerah rawan pergerakan tanah di daerah Kabupaten Banyumas mengacu pada Sistem Informasi Geografis (SIG) dengan menggunakan metode information value model dan frequency ratio. Tujuan lainnya yaitu untuk mengkaji tingkat akurasi dari setiap metode dan menentukan metode apakah yang lebih baik digunakan di lokasi penelitian. Hasil dari penelitian ini didapatkan bahwa model yang dihasilkan oleh metode frekuensi rasio mendapatkan nilai AUC pada succes rate sebesar 70,5% dan predictife rate 61,14%. Sementara model yang dihasilkan oleh metode information value mendapatkan nilai AUC succes rate sebesar 66,39% dan predictife rate 60,26%. Berdasarkan validasi AUC dari kedua model tersebut, maka diketahui metode frekuensi rasio merupakan metode yang lebih baik dari metode information value dalam memodelkan tingkat kerentanan gerakan tanah di lokasi penelitian.

---

Land movement is a process when soil or rock material is displaced due to the earth's gravity and the impact is detrimental to the environment and causes casualties (Noor, 2011). Based on records from the National Disaster Management Agency, there were 289 disaster events due to land movement from 2018 to 2022 in Banyumas Regency, Central Java Province (Disaster Information Data Indonesia (DIBI)). Land movement is influenced by parameters that affect land movement such as lithology, slope aspect, curvature, rainfall, slope, elevation, land use, distance from rivers, distance from structures, and normalized difference vegetation index (NDVI) (Chen et al., 2021). The purpose of this research is to identify land movement prone areas based on these parameters and map land movement prone areas in the Banyumas Regency area referring to the Geographic Information System (GIS) using the information value model and frequency ratio methods. Another objective is to assess the accuracy level of each method and determine which method is better used in the research location. The results of this study found that the model generated by the frequency ratio method obtained an AUC value at a success rate of 70.5% and a predictive rate of 61.14%. While the model produced by the information value method gets an AUC succes rate of 66.39% and a predictive rate of 60.26%. Based on the AUC validation of the two models, it is known that the frequency ratio method is a better method than the information value method in modeling the level of ground motion vulnerability at the research site."

"Gempa dan rangkaian fenomena khusus di Palu dan berbagai belahan dunia mengakibatkan likuifaksi yang melibatkan korban jiwa dan kerugian ekonomi yang luar biasa. Evaluasi potensi likuifaksi berdasarkan data standard penetration test (SPT) menggunakan pendekatan deterministik telah digunakan secara luas. Model indeks likuifaksi diperlukan untuk penetapan kurva kondisi batas antara kasus likuifaksi dan non-likuifaksi dengan mempertimbangkan masalah bias dalam metode deterministik. Penelitian ini bertujuan untuk menetapkan model indeks likuifaksi sebagai relasi antara (N1)60 dan CSR7,5 menggunakan multi-gene genetic programming (MGGP) untuk penyusunan kurva kondisi batas dan perbandingannya dengan model dari penelitian terdahulu. Model indeks likuifaksi yang dibangun berdasarkan data SPT menggunakan MGGP menghasilkan performa keberhasilan prediksi 93% untuk testing datasets.

---

Earthquake and series of specific phenomena in Palu and any other parts of the world contributed to a liquefaction that was involving massive fatalities and economic loss. The evaluation of liquefaction potential based on standard penetration test (SPT) data using deterministic approach has been widely applied. A liquefaction index model is required for the determination of a limit state between liquefaction and non-liquefaction cases by the consideration of bias issues in deterministic method. This research is aimed at the determination of liquefaction index model in relating (N1)60 and CSR7.5 using multi-gene genetic programming (MGGP) to develop limit state curve and its comparison with previous studies. The developed liquefaction index model based on SPT data using MGGP resulted in a performance in terms of successful prediction of 93% for testing of datasets."

"Dengan adanya perubahan peraturan SNI 1726 “Standar perencanaan ketahanan gempa untuk struktur bangunan Gedung”, maka bangunan yang lama akan mengalami penambahan beban gempa. Untuk mengembalikan beban gempa ke nilai awal dapat dilakukan dengan menggunakan isolator. Untuk penelitian ini isolator yang digunakan ialah lead rubber bearing dan ditempatkan pada lantai paling atas bangunan lalu menambah beban diatas lead rubber bearing. Objek pada penelitian ini ialah bangunan dengan denah berbentuk L yang akan divariasikan sebanyak 10 model berisolator dan 1 model fix-based. Hasil dari penelitian ini akan menganalisa pengaruh variasi beban dan kekakuan lead rubber bearing terhadap respons struktur bangunan, Analisa yang digunakan ialah Analisa respons spektrum dengan parameter yang dibandingkan meliputi: periode getar, gaya geser tingkat, simpangan antar lantai dan pusat massa. Berdasarkan hasil penelitian menggunakan analisa respon spektrum, penggunaan lead rubber bearing dapat mengurangi gaya geser dasar akibat gempa berkisar antara 19-23

---

With the amendment of SNI 1726 regulation "Standards for planning earthquake resistance for building structures", old buildings will experience additional earthquake loads. In order to restore the earthquake load to the initial value, it can be done using an isolator.The isolator that is used for this study is lead rubber bearing, and it is placed on the top floor of the building and then added an additional load at the top of lead rubber bearing. The object of this study is a building with an L-shaped plan with variation of 10 isolated models and 1 fix based model. The results of this study will analyze the structural response of buildings caused by variations in load and stiffness of lead rubber bearing on. The analysis used in this study was responses spectrum analysis with parameters that being compared covers: period of vibration, story shear, intersection between floor and center of mass. Based on the results of the study using response spectrum analysis, the use of lead rubber bearings can reduce the base shear due to earthquakes ranging from 19-23%."