Dinda Aulia Pramesto, - (2019) APLIKASI PENENTUAN NILAI PREMI UNTUK ASURANSI JIWA MENGGUNAKAN GENERALIZED LINEAR MIXED MODEL (GLMM). S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
ABSTRAK Penelitian ini bertujuan untuk menghitung harga premi berdasarkan faktor underwriting dan faktor frailty dengan metode Generalized Linear Mixed Model (GLMM). GLMM digunakan untuk memodelkan gabungan antara efek tetap (faktor underwriting) dan efek acak (faktor frailty) antar individu. Data yang digunakan adalah data longitudinal mengenai faktor underwriting yang diperoleh dari Health and Retirement Study dan diolah menggunakan Rstudio. Data yang digunakan merupakan data dengan selang waktu dua tahun, sehingga probabilitas kematian yang diperoleh adalah untuk dua tahun kedepan. Faktor underwriting yang berpengaruh secara signifikan terhadap model probabilitas kematian adalah usia, alkohol, dan jantung sehingga diperoleh model probabilitas kematian setiap individu untuk menentukan nilai premi. Penentuan nilai premi diperoleh dengan bantuan program aplikasi yang dibuat dengan bahasa pemrograman Java. Nilai premi setiap individu besarnya berbeda bergantung pada faktor underwriting dan frailty. Kata Kunci: Generalized Linear Mixed Model, unterwriting, frailty, data longitudinal. ABSTRACT The purpose of this study is to determine premium based on underwriting factors and frailty factors using Generalized Linear Mixed Model (GLMM). GLMM is used for modeling a combination of fixed effect (underwriting) and random effect (frailty) between individuals. The longitudinal data about underwriting that are taken from Health and Retirement Study are used in this study and it is processed by using Rstudio. The data used are data with an interval of two years, so the probability of death is obtained for the next two years. Underwriting factors that have a significant effect on the probability of death model are age, alcohol, and heart disease, so that the probability of death of each individual is obtained to determine the life isnurance premium. Determination of the premium is calculated by applications that have been made by the Java programming language. The premium for each individual is different depending on the underwriting and frailty factors. Keywords: Generalized Linear Mixed Model, underwriting, frailty, longitudinal data.
| Item Type: | Thesis (S1) |
|---|---|
| Uncontrolled Keywords: | Generalized Linear Mixed Model, unterwriting, frailty, data longitudinal. |
| Subjects: | L Education > L Education (General) Q Science > QA Mathematics |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Matematika (non kependidikan) |
| Depositing User: | Dinda Aulia Pramesti |
| Date Deposited: | 09 Mar 2020 09:14 |
| Last Modified: | 09 Mar 2020 09:14 |
| URI: | http://repository.upi.edu/id/eprint/38887 |
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