Main Article Content

Abstract

Agriculture plays an important role in national economic development. However, it has the highest risk of loss due to its dependence on climate conditions. One of the efforts to reduce the risk of crop failure is through an agricultural insurance program. This study aimed to analyze the value of the rainfall climate index used and the calculation of agricultural insurance premiums based on it. The method used to determine the rainfall climate index was the historical burn analysis method, while the method used to calculate agricultural insurance premiums was the Black-Scholes method. The study showed significant spatial variation in rainfall index-based agricultural insurance premiums across Sumatra. Premiums rose with higher percentiles, with North Sumatra the highest (IDR 3.28–3.55 million) and Aceh the lowest (IDR 100–137 thousand). The inclusion of all rainfall stations revealed a more detailed spatial pattern. Overall, premiums strongly reflect local climatic conditions and can aid risk assessment and insurance planning.

Keywords

Rainfall Index Insurance Black-Scholes Agricultural Risk Management Weather Derivatives Premium Calculation

Article Details

How to Cite
Lestari, F., Julianty, D. T., & Vikarti, M. M. (2026). Black-Scholes Method for Rainfall Index-Based Agricultural Insurance Premiums . Enthusiastic : International Journal of Applied Statistics and Data Science, 6(1), 69–81. https://doi.org/10.20885/enthusiastic.vol6.iss1.art7

References

  1. C. Stutley, “ASEAN Guideline on Agricultural Insurance Implementation: Lessons and Experience from the ASEAN Countries,” Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Bonn, Germany, 2022.
  2. R.M. Hohl, Agricultural Risk Transfer: From Insurance to Reinsurance to Capital Markets, 1st ed. Chichester, United Kingdom: John Wiley & Sons Ltd, 2019, ch. 1, pp. 21–25, doi: 10.1002/9781119560462.
  3. P. Djunedi, “Analisis asuransi pertanian di Indonesia: Konsep, tantangan, dan prospek,” J. Borneo Adm., vol. 12, no. 1, pp. 9–27, Jun. 2016, doi: 10.24258/jba.v12i1.209.
  4. A. Leblois and P. Quirion, “Agricultural insurance based on meteorological indices: Realizations, methods and research challenges,” Meteorol. Appl., vol. 20, no. 1, pp. 1–9, Mar. 2013, doi: 10.1002/met.1296.
  5. D. Ariyanti, R. Riaman, and I. Irianingsih, “Application of historical burn analysis method in determining agricultural premium based on climate index using Black Scholes method,” JTAM, vol. 4, no. 1, pp. 28–32, Apr. 2020, doi: 10.31764/jtam.v4i1.1799.
  6. D.G. Luenberger, Investment Science. New York, NY, USA: Oxford University Press, 1998.
  7. F. Lestari et al., Pengantar Matematika Aktuaria. Jakarta, Indonesia: PT. Scifintech Andrew Wijaya, 2022, ch. 10, pp. 140–141.
  8. N.S. Seftiani, N. Satyahadewi and N.M. Huda, “Penerapan model harga opsi Black Scholes dalam penentuan premi asuransi jiwa dwiguna unit link,” Euler, J. Ilm. Mat. Sains Teknol., vol. 11, no. 2, pp. 318–327, Dec. 2023, doi: 10.37905/euler.v11i2.23049.
  9. Badan Meteorologi, Klimatologi, dan Geofisika (BMKG), Buku Informasi Normal Curah Hujan Indonesia 1991-2020. Jakarta, Indonesia: BMKG, 2020.
  10. S.C. Chapra and R.P. Canale, Numerical Methods for Engineers, 7th ed. New York, NY, USA: McGraw-Hill Education, 2015.
  11. W. Estiningtyas, “Pengembangan model asuransi indeks meningkatkan ketahanan petani padi dalam menghadapi perubahan iklim,” Ph.D. dissertation, Dept. Geophys. Meteorol., Institut Pertanian Bogor, Bogor, Indonesia, 2012.
  12. International Research Institute for Climate and Society (IRI), “Weather Index Insurance Education,” 2010. Accessed: May 20, 2025. [Online]. Available: http://wiiedu.iri.columbia.edu
  13. R.G. Allen, L.S. Pereira, D. Raes, and M. Smith, Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. (1998). Accessed: 1 March 2025. [Online]. Available: https://appgeodb.nancy.inrae.fr/biljou/pdf/Allen_FAO1998.pdf
  14. N.D. Rahayu, B. Sasmito, and N. Bashit, “Analisis pengaruh fenomena Indian Ocean Dipole (IOD) terhadap curah hujan di Pulau Jawa,” J. Geod. Undip, vol. 7, no. 1, pp. 57–67, Jan. 2018.
  15. K.R. Subramanyam and J.J. Wild, Financial Statement Analysis, 10th ed. New York, NY, USA: McGraw-Hill Irwin, 2009.
  16. K.A. Sidarto, M. Syamsuddin, and N. Sumarti, Matematika Keuangan. Bandung, Indonesia: ITB Press, 2019.
  17. G. Marola, N. Satyahadewi, and W. Andani, “Application of the Black Scholes method for counting agricultural insurance premium price based on rainfall index in Kapuas Hulu Regency,” BAREKENG, J. Ilm. Mat. Terap., vol. 17, no. 2, pp. 819–826, Jun. 2023, doi: 10.30598/barekengvol17iss2pp0819-0826.
  18. J.C. Hull, Options, Futures, and Other Derivatives, 9th ed. Upper Saddle River, NJ, USA: Pearson Education, 2015.
  19. D.C.M. Dickson, M.R. Hardy, and H.R. Waters, Actuarial Mathematics for Life Contingent Risks. New York, NY, USA: Cambridge University Press, 2009, doi: 10.1017/CBO9780511800153.
  20. M.M. Vikarti and F. Lestari, “Perhitungan premi asuransi pertanian berdasarkan indeks iklim curah hujan dengan menggunakan metode Black-Scholes di Provinsi Lampung,” J. Lebesgue J. Ilm. Pendidik. Mat., Mat. Stat., vol. 6, no. 1, pp. 461–472, Mar. 2025, doi: 10.46306/lb.v6i1.956.
No Related Submission Found