Penentuan premi asuransi bencana alam dengan metode Buhlmann-Straub, sistem subsidi, dan sistem subsidi silang di Indonesia

Altrawidadi, Fabianus (2024) Penentuan premi asuransi bencana alam dengan metode Buhlmann-Straub, sistem subsidi, dan sistem subsidi silang di Indonesia. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Pemilihan metode yang sesuai dengan data merupakan salah satu langkah yang penting dalam proses penentuan premi asuransi bencana alam. Metode Buhlmann Straub adalah metode yang umum digunakan dalam penentuan premi asuransi secara non parametrik. Data indeks risiko bencana alam, Produk Domestik Regional Bruto Harga Konstan (PDRBHK), dan jumlah kejadian bencana setiap provinsi di Indonesia memberikan ruang bagi peneliti untuk meneliti metode subsidi dan metode subsidi silang. Penentuan metode dan parameter yang tepat memerlukan pengamatan yang cukup banyak dalam sebuah proses penelitian, dikarenakan banyaknya kombinasi yang dapat menentukan hasil dari setiap variabel. Hasil penelitian metode subsidi dan metode subsidi silang menggunakan empat jenis perlakuan perhitungan yang berbeda, yaitu: (i) Klasifikasi provinsi dihitung dengan rasio indeks risiko, besarnya subsidi dihitung dengan rasio PDRBHK, dan faktor penambah subsidi dihitung dengan rasio jumlah kejadian bencana alam ( r, s, n), (ii) Klasifikasi provinsi dihitung dengan rasio indeks risiko, besarya subsidi dihitung dengan rasio jumlah kejadian bencana alam, dan faktor penambah subsidi dihitung dengan rasio PDRBHK (r,n,s), (iii) Klasifikasi provinsi dihitung dengan rasio PDRBHK, besarya subsidi dihitung dengan rasio indeks risiko, dan faktor penambah subsidi dihitung dengan rasio jumlah kejadian bencana ( s, r, n), dan (iv) Klasifikasi provinsi dihitung dengan rasio PDRBHK, besarya subsidi dihitung dengan rasio jumlah kejadian bencana, dan faktor penambah subsidi dihitung dengan rasio indeks risiko bencana ( s, n, r). Jika dibandingkan melalui proses analisis persentase perubahan dan dengan uji beda, dapat disimpulkan jenis perlakukan r, n, s merupakan metode yang terbaik. Metode terbaik diartikan bahwa hasilnya sesuai dengan definisi dari subsidi, subsidi yang beragam antar provinsi, dan eror yang kecil dibandingkan dengan data aktual. / The selection of an appropriate method aligned with the data is a crucial step in determining natural disaster insurance premiums. The Buhlmann-Straub method is commonly used in non-parametric insurance premium determination. Data on the index of natural disaster risk, Regional Gross Domestic Product Constant Price (RGDPCP), and the number of disaster occurrences in each province in Indonesia provide scope for researchers to examine subsidy methods and cross-subsidy methods. Determining the right method and parameters requires a significant amount of observation in a research process due to the multitude of combinations that can determine the outcome of each variable. The research outcomes of the subsidy method and cross-subsidy method utilize four types of different calculation treatments, namely: (i) Provinces classification calculated with the risk index ratio, the subsidy amount calculated with the RGDPCP ratio, and the additional subsidy factor calculated with the ratio of the number of natural disaster occurrences (r,s,n), (ii) Provinces classification calculated with the risk index ratio, the subsidy amount calculated with the ratio of the number of natural disaster occurrences, and the additional subsidy factor calculated with the RGDPCP ratio (r,n,s), (iii) Provinces classification calculated with the RGDPCP ratio, the subsidy amount calculated with the risk index ratio, and the additional subsidy factor calculated with the ratio of the number of disaster occurrences ( s, r, n), and (iv) Provinces classification calculated with the RGDPCP ratio, the subsidy amount calculated with the ratio of the number of natural disaster occurrences, and the additional subsidy factor calculated with the ratio of disaster risk index ( s, n, r). When compared through the percentage change analysis and difference tests, it can be said that the r, n, s treatment type is a more ideal method. The best method means that the results are under the definition of subsidies, subsidies vary between provinces, and the error is small compared to actual data.

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