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APPLICATION OF THE BLACK SCHOLES METHOD FOR COUNTING AGRICULTURAL INSURANCE PREMIUM PRICE BASED ON RAINFALL INDEX IN KAPUAS HULU REGENCY

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · pp. 0819–0826

DOI
10.30598/barekengvol17iss2pp0819-0826
ISSN
2615-3017, 1978-7227
Published
2023-06-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

High-intensity rainfall is one of the factors that can interfere with the state of agriculture. Agricultural insurance is an insurance that can be used to reduce risks related to agricultural losses such as rice production. Climate-based agricultural insurance is a management of climate-related risks. This study aims to determine the rainfall index and calculate the value of agricultural insurance premiums based on the climate index (rainfall) in Kapuas Hulu Regency using the Black Scholes method. In calculating the value of agricultural insurance premiums based on the rainfall index, it starts by calculating the value of the correlation coefficient between rainfall and rice production. Then the value of the rainfall index is obtained, which then the value of the index is tested for lognormality to meet the assumptions on the Black Scholes method, after which it calculates the ln return value of the index value obtained, the last step is to calculate the value of agricultural insurance premiums. Based on case studies, the results obtained are when the risk-free interest rate is 3.5% and rainfall is 54.23 mm the premium paid is Rp 2,386,824 and when the rainfall is 75.39 mm the premium paid is Rp 3,898,142. If the risk-free interest rate is 4% and the bulk is 54.23 mm, the premium paid is IDR 2,383,842, and when the rainfall is 75.39 mm the premium paid is IDR 3,893,272. When the risk-free interest rate is 5% and rainfall is 54.23 mm the premium paid is Rp 2,377,890 and if the rainfall is 75.39 mm the premium paid is Rp 3,883,551. So, the higher the rainfall, the greater the premium value payment. If the risk-free interest rate gets bigger then the premium payment will be smaller.

Collaboration network of the authors

40 authors · 100 co-authorship links · showing the 40 most connected

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Co-authorOrganisationJoint articles
Hendra PerdanaAffiliation unknown11
Evy SulistianingsihAffiliation unknown10
Ray TamtamaAffiliation unknown4
Shantika MarthaAffiliation unknown4
Siti AprizkiyandariAffiliation unknown2
Rita ApriliyantiAffiliation unknown2
Maria Welita DwinandaAffiliation unknown2
Rifkah Alfiyyah SaryAffiliation unknown2
Dadan KusnandarAffiliation unknown1
Hani Dwi RetnaniAffiliation unknown1
Inggriani Millennia TaralyAffiliation unknown1
Steven Jansen SinagaAffiliation unknown1
Tiffany ArdhithaAffiliation unknown1
Indah OktavianiAffiliation unknown1
Widad ImtiyazAffiliation unknown1
Dinda TiaraAffiliation unknown1
Fritzgerald Muhammad ArsyiAffiliation unknown1
Aditya Nugraha PratamaAffiliation unknown1
Naomi Nessyana DebatarajaAffiliation unknown1
Nurfitri Imro'ahAffiliation unknown1
Herina MarlisaAffiliation unknown1
Wiji UmiatiAffiliation unknown1
Ainun ZakiahAffiliation unknown1
Noerul HaninAffiliation unknown1
Della ZariaAffiliation unknown1
Muhammad FauzanAffiliation unknown1
Nabila Izza HarnantaAffiliation unknown1
Hendri AgustonoAffiliation unknown1
Rifki PebriyandiAffiliation unknown1
Risky GunawanAffiliation unknown1
Cinta Priscillia MaharaniAffiliation unknown1
David Jordy DhandioAffiliation unknown1
Hairil Al-HamAffiliation unknown1
Preatin PreatinAffiliation unknown1
Nurhanifa NurhanifaAffiliation unknown1
Louis Putra JayaAffiliation unknown1
Hendri KurniawanAffiliation 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">APPLICATION OF THE BLACK SCHOLES METHOD FOR COUNTING AGRICULTURAL INSURANCE PREMIUM PRICE BASED ON RAINFALL INDEX IN KAPUAS HULU REGENCY</dc:title>
	<dc:creator>Marola, Geby</dc:creator>
	<dc:creator>Satyahadewi, Neva</dc:creator>
	<dc:creator>Andani, Wirda</dc:creator>
	<dc:description xml:lang="en-US">High-intensity rainfall is one of the factors that can interfere with the state of agriculture. Agricultural insurance is an insurance that can be used to reduce risks related to agricultural losses such as rice production. Climate-based agricultural insurance is a management of climate-related risks. This study aims to determine the rainfall index and calculate the value of agricultural insurance premiums based on the climate index (rainfall) in Kapuas Hulu Regency using the Black Scholes method. In calculating the value of agricultural insurance premiums based on the rainfall index, it starts by calculating the value of the correlation coefficient between rainfall and rice production. Then the value of the rainfall index is obtained, which then the value of the index is tested for lognormality to meet the assumptions on the Black Scholes method, after which it calculates the ln return value of the index value obtained, the last step is to calculate the value of agricultural insurance premiums. Based on case studies, the results obtained are when the risk-free interest rate is 3.5% and rainfall is 54.23 mm the premium paid is Rp 2,386,824 and when the rainfall is 75.39 mm the premium paid is Rp 3,898,142. If the risk-free interest rate is 4% and the bulk is 54.23 mm, the premium paid is IDR 2,383,842, and when the rainfall is 75.39 mm the premium paid is IDR 3,893,272. When the risk-free interest rate is 5% and rainfall is 54.23 mm the premium paid is Rp 2,377,890 and if the rainfall is 75.39 mm the premium paid is Rp 3,883,551. So, the higher the rainfall, the greater the premium value payment. If the risk-free interest rate gets bigger then the premium payment will be smaller.</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/7813</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0819-0826</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; 0819-0826</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/7813/5943</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Geby Marola, Neva Satyahadewi, Wirda Andani</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>