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Putra, Hengki Eko
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Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Engineering

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PRICING RESIDENTIAL EARTHQUAKE INSURANCE IN INDONESIA Anwar, Alief Glenfico; Qoyyimi, Danang Teguh; Putra, Hengki Eko
MEDIA STATISTIKA Vol 17, No 2 (2024): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.17.2.150-161

Abstract

Adaptive Social Protection (ASP) is a framework that integrates social protection, disaster risk reduction, and climate change adaptation to enhance resilience against shocks and hazards. As a country vulnerable to earthquakes, Indonesia faces threats of losses due to seismic disasters. The national budget available to cover these losses can only address 13.6% of the total disaster-related losses. This study proposes an earthquake insurance scheme to protect all residences in Indonesia as part of the ASP framework, followed by the calculation of premium rates for this insurance scheme. This study utilizes the built-in OpenQuake calculator known as the probabilistic event-based risk calculator to simulate annual earthquake losses over a period of 10,000 years. The negative binomial distribution and the Pareto IV distribution are assessed as the most optimal models in modeling frequency and severity through distribution fitting. The application of collective risk models and the principle of pure premium results in a pure premium rate of 0.3994073 ‰. This pure premium rate can serve as a starting point in the establishment of comprehensive residential earthquake insurance in Indonesia.
KAJIAN KETIDAKPASTIAN ESTIMASI CURAH HUJAN SATELIT TRMM STUDI KASUS: DAS CILIWUNG Syahputra, Muhammad Ridho; Fajary, Faiz Rohman; Riawan, Edi; Suwarman, Rusmawan; Putra, Hengki Eko
Bulletin of Geology Vol 6 No 3 (2023): Bulletin of Geology
Publisher : Fakultas Ilmu dan Teknologi Kebumian (FITB), Institut Teknologi Bandung (ITB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/bull.geol.2022.6.3.4

Abstract

Dataset curah hujan (CH) dengan resolusi spasial dan temporal yang baik diperlukan oleh berbagai sector seperti sektor manajemen sumber daya air dan bencana hidrologi. Namun, pengamatan CH secara langsung di permukaan seringkali tidak lengkap dan tidak merata. Sumber alternatif data CH lainnya dapat diperoleh dari estimasi CH oleh satelit (penginderaan jauh). Namun, estimasi satelit memiliki kesalahan dan ketidakpastian yang berpotensi mempengaruhi aplikasi selanjutnya yang menggunakan data hujan. Oleh karena itu, penting untuk mengukurketidakpastian estimasi CH satelit untuk memberikan informasi tambahan bagi pengguna mengenai keandalan data. Pada penelitian ini telah dilakukan simulasi Monte Carlo untuk menghasilkan ensemble Dataset CH yang mampu mengkuantifikasi ketidakpastian produk estimasi CH TRMM (Tropical Rainfall Measuring Mission) 3B43v7. Dataset CH ensemble ini dapat digunakan untuk memberikan informasi tentang distribusi error dan estimasi peluang CH dari estimasi satelit TRMM. Dalam kajian ini juga ditunjukkan pemanfaatan dataset CH ensemble dalam mengkuantifikasi ketidakpastian dalam analisis CH ekstrim menggunakan pendekatan periode ulang dan Probable Maximum Precipitation (PMP). Kata kunci: estimasi satelit, TRMM, ketidakpastian, Monte Carlo, ensemble
Co-Authors Anwar, Alief Glenfico Edi Riawan, Edi Fajary, Faiz Rohman Qoyyimi, Danang Teguh Suwarman, Rusmawan Syahputra, Muhammad Ridho