Abstract
An empirical study to develop benchmark models at country-level to assess the suggested number of earthquake strongmotion stations based on a framework encompassing geographic, demographic, and socio-economic parameters is reported. The models are to provide a working estimate of the required number of stations for improving the strongmotion instrumentation program of Indonesia. National earthquake strong-motion networks of New Zealand, Japan, Taiwan, Iran, Turkey, and Italy were used as the references. The parameter proposed is the number of stations in land area of 1,000 km2, and three models based on the exponential regression analysis are presented as functions of population density, Gross Domestic Product (GDP) per capita, and the Global Competitiveness Index (GCI) Basic Requirements Index. Using the models, it is suggested that Indonesia would require at least 750 stations.
Bahasa Abstract
Model Acuan Tingkatan Negara untuk Program Sistem Pencatat Percepatan Gempabumi Kuat. Makalah ini memaparkan hasil pengembangan beberapa model acuan untuk menentukan jumlah stasiun pencatat percepatan gempabumi kuat pada tingkatan negara berdasarkan kondisi geografis, demografis, dan sosial-ekonomi. Beberapa model ini dapat digunakan dalam pengembangan lebih lanjut sistem pencatat gempa bumi kuat Indonesia. Dasar pengembangan model adalah sistem serupa di Selandia Baru, Jepang, Taiwan, Iran, Turki, dan Italia. Parameter jumlah stasiun pencatat yang diusulkan adalah jumlah stasiun per 1000 km2 luas daratan, dan tiga buah model regresi eksponensial telah dikembangkan berdasarkan fungsi kepadatan penduduk negara, fungsi Produk Domestik Bruto (PDB) per kapita, dan fungsi Indeks Daya-Saing Global (GCI) kelompok Persyaratan Dasar. Berdasarkan tiga model ini, jumlah minimum stasiun pencatat yang dibutuhkan adalah sekitar 750 stasiun.
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Recommended Citation
Prakoso, Widjojo Adi and Sukanta, I Nyoman
(2012)
"Benchmark for Country-Level Earthquake Strong-Motion Instrumentation Program,"
Makara Journal of Technology: Vol. 16:
Iss.
2, Article 6.
DOI: 10.7454/mst.v16i2.1511
Available at:
https://scholarhub.ui.ac.id/mjt/vol16/iss2/6
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