| dc.contributor.advisor | Ruhiyat | |
| dc.contributor.advisor | Agustiani, Nur | |
| dc.contributor.author | Annisa, Fakhira | |
| dc.date.accessioned | 2025-07-18T08:43:14Z | |
| dc.date.available | 2025-07-18T08:43:14Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/165312 | |
| dc.description.abstract | Seiring bertambahnya usia, risiko disabilitas pada usia lanjut turut meningkat sehingga mendorong kebutuhan akan asuransi long term care (LTC) sebagai perlindungan terhadap biaya perawatan jangka panjang. Penelitian ini bertujuan untuk menentukan premi tahunan bersih LTC dengan pendekatan multistate berdasarkan data prevalensi disabilitas, serta mempertimbangkan ketidakpastian suku bunga melalui model stokastik Cox-Ingersoll-Ross (CIR). Hasil pemodelan menunjukkan bahwa model CIR mampu memprediksi suku bunga BI-7 Day Reverse Repo Rate (BI7DRR) dengan akurasi yang baik, ditunjukkan oleh nilai MAPE sebesar 6.95% pada data training dan 3.7% pada data testing. Perbandingan premi menunjukkan bahwa penggunaan suku bunga stokastik CIR menghasilkan premi yang lebih rendah dibandingkan dengan suku bunga konstan, seiring dengan nilai faktor diskon yang lebih besar. Selain itu, penerapan skema kenaikan gaji tahunan menghasilkan premi awal yang lebih rendah. Meskipun begitu, nominal premi meningkat dan akan melebihi premi konstan pada tahun tertentu. | |
| dc.description.abstract | As individuals age, the risk of disability in old age increases, thereby driving the need for Long-Term Care (LTC) insurance as financial protection against the high costs of long-term care services. This study aims to determine the annual net premium of LTC insurance using a multistate model based on adjusted disability prevalence data, while also incorporating interest rate uncertainty through the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. The modeling results show that the CIR model is capable of predicting the BI-7 Day Reverse Repo Rate (BI7DRR) with good accuracy, indicated by MAPE values of 6.95% for training data and 3.7% for testing data. The premium comparison reveals that using the stochastic CIR model results in lower premiums compared to a constant interest rate assumption, due to the higher average discount factor. Furthermore, the implementation of an annual salary increase scheme leads to a lower initial premium. However, the nominal premium increases over time and eventually exceeds the constant premium at certain policy years. | |
| dc.description.sponsorship | Beasiswa Harry Diah AAJI (BHD AAJI) | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Penentuan Premi Tahunan Bersih pada Asuransi Long-Term Care dengan Suku Bunga Stokastik Model Cox-Ingersoll-Ross | id |
| dc.title.alternative | | |
| dc.type | Skripsi | |
| dc.subject.keyword | model CIR | id |
| dc.subject.keyword | premi | id |
| dc.subject.keyword | CIR model | id |
| dc.subject.keyword | interest rate | id |
| dc.subject.keyword | premium | id |
| dc.subject.keyword | asuransi LTC | id |
| dc.subject.keyword | model multistate | id |
| dc.subject.keyword | suku bunga stokastik | id |
| dc.subject.keyword | LTC insurance | id |
| dc.subject.keyword | multistate model | id |