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Journal : International Journal of Quantitative Research and Modeling

Premium Sufficiency Reserve on Joint Life Insurance with Laplace Distribution Triyuni, Meisy; Sirait, Haposan
International Journal of Quantitative Research and Modeling Vol. 6 No. 3 (2025): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i3.1074

Abstract

Each insurance participant pays a premium to the insurance company during the coverage period. In paying the sum insured to insurance participants, insurance companies need to prepare reserve costs. This reserve fee is used to pay for the needs of insurance companies and insurance participants. This research explains the calculation of premium sufficiency reserve for joint life insurance for life insurance participants aged x years and y years with Laplace distribution. The parameters of the Laplace distribution are estimated using the method of momen and the method of maximum likelihood. The solution of the problem is obtained by determining the initial life annuity term, single premium, and annual premium so that the premium sufficiency reserve formula based on Laplace distribution is obtained. The results of the calculation of premium sufficiency reserves of joint life insurance using Laplace distribution are more less the same as the prospective reserves of joint life insurance using Laplace distribution.
Application of Structural Equations Modeling Partial Least Square at the Comparation of the Niveau of Responsibility From Cs and Digics Pradana, Visca Nadia; Sirait, Haposan
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.604

Abstract

Banking is an institution that plays a role in increasing economic development and also increasing equitable development. People who are serving users will be more selective in choosing banks so that many banks strive to be superior and more satisfying than other banks. Customer satisfaction can be seen from the role of CS and DigiCS. Customer Service ( CS ) is all actions intended to meet needs and activities by providing services so that each customer's needs are met. Digital Customer Service (DigiCS) is BNI digital banking automation that provides customers with immediate experience when carrying out digital transactions at BNI . The aim of this research is to determine the factors that influence the level of CS and DigiCS customer satisfaction with several variables, namely product quality ( ), service quality ( ), time ( ), convenience/efficiency ( ), and customer satisfaction (Y). The method used in this research is structural equation modeling partial least squares with the help of Microsoft Excel and SmartPLS software with the application of SEM - PLS to analyze the relationship between endogenous latent variables and exogenous latent variables. The results of this research are that for CS customer satisfaction it is found that only the exogenous variable product quality ( ) with its influences indicators customer satisfaction (Y) while for DigiCS customer satisfaction the results are that only the exogenous variable product quality ( ) and the exogenous variable convenience/efficiency ( ) with indicators that influence customer satisfaction (Y).
Survival Analysis of Patients with Kidney Failure at Arifin Achmad Hospital, Riau Province using the Kaplan-Meier Method Sanurtillah, Farissa; Sirait, Haposan
International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i2.689

Abstract

The importance of applying advanced mathematical models in bond investing marks a revolutionary step in the modern financial industry, enabling more scalable and adaptive strategies to achieve financial success. The purpose of this talk is to explore and detail the role of advanced mathematical models in changing the bond investment paradigm. The discussion aims to highlight the crucial role of advanced mathematical models in changing the bond investment paradigm, providing a deeper understanding of the optimal potential and risks involved, explaining how this approach can optimize financial outcomes through more detailed analysis. The application of mathematical models involves the use of sophisticated algorithms and statistical analysis to identify optimal investment opportunities. These steps include the use of advanced financial math formulas, such as yield to maturity and duration, to design investment strategies that are adaptive and responsive to bond market dynamics. The application of mathematical models results in a deeper understanding of the bond market, allowing investors to respond quickly to changing market conditions. Thus, the investment strategy formed by this approach can not only improve investment returns, but also reduce the risks that investors may face. The application of advanced mathematical models in bond investing opens the door to smarter and more informed decision-making. By combining data and mathematical analysis, investors can maximize potential investment returns and manage risks more effectively.