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Open access Jurnal SINTA 3

NET SINGLE PREMIUM ON CRITICAL ILLNESS INSURANCE WITH MULTI-STATE MODEL

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · pp. 0989–0994

DOI
10.30598/barekengvol17iss2pp0989-0994
ISSN
2615-3017, 1978-7227
Published
2023-06-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The chances of someone getting a disease or suffering from a critical illness are very large, especially when they get older, the chances of getting a critical illness will be higher. A guarantee of the future is indispensable if a person suffers from a critical illness at any time and requires considerable costs to undergo treatment. Insurance is one of the right choices and is beneficial for people with critical illnesses. In this study, the calculation of Critical Illness insurance premiums was carried out to determine the value of premiums that must be paid by a person when suffering from a critical illness. The types of critical illnesses used include cancer, heart disease, stroke, kidney failure, diabetes mellitus, and hypertension. Health insurance that protects insureds suffering from critical illnesses is Long Term Care insurance with the Annuity as A Rider Benefit product. The multi-state model is used to determine the probability of a person suffering from a critical illness. The benefits obtained are in the form of death compensation, and treatment costs when the insured is diagnosed with a critical illness. The data used are data on the prevalence of critical illnesses and the percentage of deaths due to critical illnesses. In this study, we will compare the amount of premium that must be paid by the insured with different interest rates, gender, coverage period, and age. The higher the age at the beginning of following the insurance, the higher the premium. The higher the interest rate during the payer's period, the lower the premium.

Collaboration network of the authors

39 authors · 88 co-authorship links

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Co-authorOrganisationJoint articles
Evy SulistianingsihAffiliation unknown10
Wirda AndaniAffiliation unknown4
Hani Dwi RetnaniAffiliation unknown4
Dadan KusnandarAffiliation unknown3
Dinda TiaraAffiliation unknown3
Steven Jansen SinagaAffiliation unknown2
Widad ImtiyazAffiliation unknown2
Fritzgerald Muhammad ArsyiAffiliation unknown2
Muhammad FauzanAffiliation unknown2
Nabila Izza HarnantaAffiliation unknown2
Nurhanifa NurhanifaAffiliation unknown2
Sania PujiantiAffiliation unknown2
Shantika MarthaAffiliation unknown1
Yundari YundariAffiliation unknown1
Setyo Wira RizkiAffiliation unknown1
Geby MarolaAffiliation unknown1
Rita ApriliyantiAffiliation unknown1
Tiffany ArdhithaAffiliation unknown1
Indah OktavianiAffiliation unknown1
Maria Welita DwinandaAffiliation unknown1
Lisa LestariAffiliation unknown1
Aditya Nugraha PratamaAffiliation unknown1
Naomi Nessyana DebatarajaAffiliation unknown1
Nurfitri Imro'ahAffiliation unknown1
Herina MarlisaAffiliation unknown1
Rifkah Alfiyyah SaryAffiliation unknown1
Ainun ZakiahAffiliation unknown1
Noerul HaninAffiliation unknown1
David Jordy DhandioAffiliation unknown1
Hairil Al-HamAffiliation unknown1
Preatin PreatinAffiliation unknown1
Louis Putra JayaAffiliation unknown1
Hendri KurniawanAffiliation unknown1
Yuyun Eka PratiwiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">NET SINGLE PREMIUM ON CRITICAL ILLNESS INSURANCE WITH MULTI-STATE MODEL</dc:title>
	<dc:creator>Taraly, Inggriani Millennia</dc:creator>
	<dc:creator>Satyahadewi, Neva</dc:creator>
	<dc:creator>Perdana, Hendra</dc:creator>
	<dc:creator>Tamtama, Ray</dc:creator>
	<dc:creator>Aprizkiyandari, Siti</dc:creator>
	<dc:description xml:lang="en-US">The chances of someone getting a disease or suffering from a critical illness are very large, especially when they get older, the chances of getting a critical illness will be higher. A guarantee of the future is indispensable if a person suffers from a critical illness at any time and requires considerable costs to undergo treatment. Insurance is one of the right choices and is beneficial for people with critical illnesses. In this study, the calculation of Critical Illness insurance premiums was carried out to determine the value of premiums that must be paid by a person when suffering from a critical illness. The types of critical illnesses used include cancer, heart disease, stroke, kidney failure, diabetes mellitus, and hypertension. Health insurance that protects insureds suffering from critical illnesses is Long Term Care insurance with the Annuity as A Rider Benefit product. The multi-state model is used to determine the probability of a person suffering from a critical illness. The benefits obtained are in the form of death compensation, and treatment costs when the insured is diagnosed with a critical illness. The data used are data on the prevalence of critical illnesses and the percentage of deaths due to critical illnesses. In this study, we will compare the amount of premium that must be paid by the insured with different interest rates, gender, coverage period, and age. The higher the age at the beginning of following the insurance, the higher the premium. The higher the interest rate during the payer's period, the lower the premium.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8059</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0989-0994</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0989-0994</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8059/5960</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Inggriani Millennia Taraly, Neva Satyahadewi, Hendra Perdana, Ray Tamtama, Siti Aprizkiyandari</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>