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All Journal Cannarium (Jurnal Ilmu-ilmu Pertanian) Tolis Ilmiah: Jurnal Penelitian Jurnal Pengabdian kepada Masyarakat Dinamika Lingkungan Indonesia Kolaborasi Jurnal Pengabdian Masyarakat ARZUSIN: Jurnal Manajemen dan Pendidikan Dasar Journal of Artificial Intelligence and Digital Business Jurnal Pengabdian Masyarakat Bangsa Journal of Mathematics and Applied Statistics Jurnal Pertanian Khairun (JPK) International Journal of Economic Research and Financial Accounting Journal of Community Empowerment Zona Kebidanan : Program Studi Kebidanan Universitas Batam
Nursamsi, Nursamsi
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Journal : Journal of Mathematics and Applied Statistics

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Calculation of Actuarial Values Using The Result of The 2019 Makeham Mortality Law Contruction and The Cox Ingersoll Ros M, Suriani; Nisardi, Muhammad Rifki; Nursamsi, Nursamsi; Hukmah, Hukmah; Sulma, Sulma
Journal of Mathematics and Applied Statistics Vol. 1 No. 1 (2023): June 2023
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v1i1.32

Abstract

Premium is an amount of money that must be paid by the customer at a certain time based on the insurance policy. This study aims to determine the value of whole life insurance premiums using the Makeham mortality law method and the Cox Ingersoll Ross (CIR) model. The result of the study obtained the calculation of interest rates using the CIR model, the smaller the  value, the greater discount and the premium paid using the Makeham mortality law method was Rp. 102.478 < premium <  Rp. 1.270.630 / Mounth.
Application of Exponential and Logistic Models in Estimating the Population of Bulukumba Regency in 2020-2030 Sulma, Sulma; Nursamsi, Nursamsi
Journal of Mathematics and Applied Statistics Vol. 1 No. 2 (2023): December 2023
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v1i2.72

Abstract

Population data is useful as planning material in making various policies, including avoiding imbalances between the number of health facilities and services and the population in an area as well as other facilities such as schools, markets, and other public facilities. Ordinary differential equations of exponential and logistic models are used in modeling population dynamics in Bulukumba Regency to obtain population estimates until 2030. The determination of the future population of Bulukumba Regency is based on the growth rate and capacity obtained using the exponential and logistic approaches. The results obtained show that the estimation using the exponential model and the logistic model estimation for 2015-2019 are close to the data from the Central Bureau of Statistics. However, the logistic model is more accurate than the exponential model which is more significantly close to the data from BPS. So that the results of the logistic model are better than the exponential. The logistic model assumes that Bulukumba Regency has a capacity of K = 450000, while the exponential model assumes that the population increases exponentially.
Co-Authors Addiarahman, Addiarahman Amirullah, Mulia Annisa, Khairun Azmar, Dwiva Deni Efizon Djumadil, Nurdiyanawati Dwijatmoko, M. Isa Fatmawati, Mila Firman syah Firmansyah, Andan Hamidin Rasulu Haris Mahmud Herman Darwis Hukmah, Hukmah Insani, Yarin Rahmat Kaddas, Fatmawati Khairun Annisa Lena Agustina M, Suriani Mangunsong, Agustinus Mardiyani Sidayat Mila Fatmawati Mira Mira Muhammad Rifki Nisardi Muhammad Syahfitra Natal Basuki Novfirman, Novfirman Nurhaliza, Nabila Nurul Aulia, Devy Lestari Orinaldi, Mohammad QOLBY, FRISKIA HANATUL Rizki Aulia, Adinda Salsabilah, Nadwa Sari, Novi Yulanda Sulma, Sulma Syahroni Syahroni Thamrin Thamrin