Penentuan Premi Asuransi Pertanian Bawang Merah dii Jawa Timur Berbasis Indeks Risiko Iklim Menggunakan Model Black-Scholes

Trunajaya, Salsabilla Arrifatul Putri Trunajaya (2026) Penentuan Premi Asuransi Pertanian Bawang Merah dii Jawa Timur Berbasis Indeks Risiko Iklim Menggunakan Model Black-Scholes. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Produksi bawang merah di Provinsi Jawa Timur rentan terhadap risiko iklim yang dapat menyebabkan penurunan produktivitas dan kerugian bagi petani. Salah satu upaya mitigasi risiko tersebut adalah melalui pengembangan asuransi pertanian berbasis indeks iklim. Penelitian ini bertujuan untuk mengidentifikasi karakteristik produktivitas bawang merah dan variabel iklim, menganalisis pengaruh variabel iklim terhadap produktivitas bawang merah menggunakan regresi data panel, serta menentukan premi asuransi pertanian bawang merah berbasis indeks iklim menggunakan model Black–Scholes. Data yang digunakan merupakan data panel tahunan pada 14 kabupaten/kota dengan produktivitas bawang merah di atas rata-rata Indonesia di Provinsi Jawa Timur selama periode 2018–2024. Variabel yang dianalisis meliputi curah hujan, suhu, dan kelembapan udara. Analisis regresi data panel dilakukan menggunakan Common Effect Model (CEM), Fixed Effect Model (FEM), dan Random Effect Model (REM). Pemilihan model terbaik dilakukan melalui uji Chow, Hausman, dan Lagrange Multiplier. Selanjutnya, premi asuransi dihitung menggunakan pendekatan option-based pricing dengan model Black–Scholes berdasarkan indeks kelembapan udara. Hasil penelitian menunjukkan bahwa Random Effect Model (REM) merupakan model terbaik untuk data panel yang digunakan. Namun, variabel curah hujan, suhu, dan kelembapan udara tidak berpengaruh signifikan terhadap produktivitas bawang merah baik secara simultan maupun parsial pada taraf signifikansi 5%. Perhitungan premi menggunakan model Black–Scholes menghasilkan premi risiko kelembapan udara rendah sebesar Rp82.804 hingga Rp24.341.769 per hektar per tahun dan premi risiko kelembapan udara tinggi sebesar Rp50.952.369 hingga Rp132.777.395 per hektar per tahun. Hasil uji sensitivitas menunjukkan bahwa volatilitas merupakan parameter yang paling berpengaruh terhadap besarnya premi.
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Shallot production in East Java Province is vulnerable to climate-related risks that may lead to productivity losses and financial damages for farmers. One approach to mitigate these risks is the development of climate index-based agricultural insurance. This study aims to identify the characteristics of shallot productivity and climate variables, analyze the influence of climate variables on shallot productivity using panel data regression, and determine climate index-based agricultural insurance premiums using the Black–Scholes model. The study employs annual panel data from 14 regencies/cities in East Java Province with shallot productivity above the national average during the 2018–2024 period. The climate variables analyzed include rainfall, temperature, and humidity. Panel data regression analysis was conducted using the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The best model was selected through the Chow test, Hausman test, and Lagrange Multiplier test. Subsequently, insurance premiums were calculated using an option-based pricing approach with the Black–Scholes model based on a humidity index. The results indicate that the Random Effect Model (REM) is the most appropriate model for the panel data used in this study. However, rainfall, temperature, and humidity were found to have no significant effect on shallot productivity, either jointly or individually, at the 5% significance level. Premium calculations using the Black–Scholes model yielded premiums for low-humidity risk ranging from IDR 82,804 to IDR 24,341,769 per hectare per year, while premiums for high-humidity risk ranged from IDR 50,952,369 to IDR 132,777,395 per hectare per year. Sensitivity analysis showed that volatility is the parameter with the greatest influence on premium values.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Asuransi Berbasis Indeks, Bawang Merah, Black–Scholes, Option-Based Pricing, Regresi Data Panel, Risiko Iklim.
Subjects:	Q Science > QA Mathematics > QA274.2 Stochastic analysis Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Salsabilla Arrifatul Putri Trunajaya
Date Deposited:	27 Jul 2026 03:36
Last Modified:	27 Jul 2026 03:36
URI:	http://repository.its.ac.id/id/eprint/137639

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