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All Journal International Journal of Business, Economics, and Social Development International Journal of Global Operations Research International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research International Journal of Humanities, Law, and Politics International Journal of Health, Medicine, and Sports International Journal of Linguistics, Communication, and Broadcasting
Lianingsih, Nestia
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Journal : International Journal of Quantitative Research and Modeling

 1 
Application of the Leslie Matrix on Female Birth Rates and Life Expectancy in the Special Region of Yogyakarta Lianingsih, Nestia; Haq, Fadiah Hasna Nadiatul; Audina, Yurid
International Journal of Quantitative Research and Modeling Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i3.761

Abstract

This study aims to predict the number and growth rate of the female population in the Special Region of Yogyakarta for 2025, using the Leslie Matrix model. The matrix utilizes fertility rates and female life expectancy across different age intervals. The data used includes the female population from 2015 and 2020, alongside Age-Specific Fertility Rate (ASFR) data for the same period. By applying the dominant eigenvalue of the Leslie matrix, the study finds that the growth rate of the female population in Yogyakarta is projected to increase, with a dominant eigenvalue of 1.252. The female population is predicted to reach 2,409,852 by 2025, an increase from 1,983,800 in 2020. These findings are expected to inform population management and development planning in Yogyakarta.
Implementation of Ruin Probability Model in Life Insurance Risk Management Lianingsih, Nestia; Hidayana, Rizki Apriva; Saputra, Moch Panji Agung
International Journal of Quantitative Research and Modeling Vol 5, No 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.816

Abstract

This study examines the implementation of the ruin probability model in risk management in life insurance companies. The main focus of this study is to evaluate how factors such as initial surplus, premium revenue level, and claim frequency affect the ruin probability of insurance companies. Using the collective risk model approach and relevant claim distribution, this study develops two methods to calculate the ruin probability: an analytical approach and a Monte Carlo simulation. The simulation results show that increasing the initial surplus and premium level significantly reduces the ruin risk, while increasing the claim frequency increases the ruin probability. In addition, the gamma claim distribution is more suitable for modeling claims in life insurance than the exponential distribution. Model validation is carried out by comparing the prediction results with historical data of insurance companies, which shows a high level of accuracy. This study provides important insights for insurance companies in designing more effective and optimal risk management strategies.
Implementation of Ruin Probability Model in Life Insurance Risk Management Lianingsih, Nestia; Hidayana, Rizki Apriva; Saputra, Moch Panji Agung
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.816

Abstract

This study examines the implementation of the ruin probability model in risk management in life insurance companies. The main focus of this study is to evaluate how factors such as initial surplus, premium revenue level, and claim frequency affect the ruin probability of insurance companies. Using the collective risk model approach and relevant claim distribution, this study develops two methods to calculate the ruin probability: an analytical approach and a Monte Carlo simulation. The simulation results show that increasing the initial surplus and premium level significantly reduces the ruin risk, while increasing the claim frequency increases the ruin probability. In addition, the gamma claim distribution is more suitable for modeling claims in life insurance than the exponential distribution. Model validation is carried out by comparing the prediction results with historical data of insurance companies, which shows a high level of accuracy. This study provides important insights for insurance companies in designing more effective and optimal risk management strategies.
Co-Authors Aglia, Arla Agung Prabowo Andrian Ibrahim, Riza AS, Nurnisaa Audina, Yurid Haq, Fadiah Hasna Nadiatul Hidayana, Rizki Apriva Ibrahim, Riza A Ibrahim, Riza Andrian Irman, Dede Jaizul , Alim Jaizul, Alim Laksito, Grida Saktian Mugi Lestari, Mugi Nurnisaa, Nurnisaa Pirdaus, Dede Irman Rini Cahyandari S, Renda Sandi Saefullah, Rifki Setyawan, Deva Putra Suhaimi, Nurnisaa binti Abdullah Sulistya A, Astrid Sulistya, Astrid Surya P, Dhika Vimelia, Willen Yohandoko, Setyo Luthfi Okta Yuningsih, Siti Hadiaty