Article Per Year (5 Year)
p-Index From 2021 - 2026
1.683
P-Index
This Author published in this journals
All Journal Journal of the Indonesian Mathematical Society Journal of Mathematical and Fundamental Sciences JOIV : International Journal on Informatics Visualization Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Kebijakan Sosial Ekonomi Kelautan dan Perikanan Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Utriweni Mukhaiyar
Statistics Research Division, Institut Teknologi Bandung, Jalan Ganesha 10 Bandung, Jawa Barat 40132, Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
COVID-19 RISK MAPPING AND LIFE INSURANCE ESTIMATION: MARKOV CHAIN MODEL FOR PREMIUMS AND BENEFITS IN BANDUNG CITY Nadwah, Hamidah Qurrotun; Mukhaiyar, Utriweni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0239-0254

Abstract

The COVID-19 pandemic, first identified in China, rapidly spread worldwide and significantly impacted various sectors, including health and insurance. In Indonesia, regional disparities in case trends have highlighted the need for localized risk assessment. This study applies a Markov Chain model to estimate life insurance premiums and benefits by forecasting long-term COVID-19 transmission probabilities across 30 sub-districts in Bandung City. The analysis uses daily confirmed case data collected between September 18, 2020, and April 17, 2022, a period marked by multiple infection waves and heightened transmission risk. COVID-19 trends were categorized into discrete states—decrease, no change, and increase—and modeled to construct transition probability matrices and stationary distributions. These long-term probabilities were then used to generate a regional risk map and inform actuarial pricing of insurance products. The results reveal spatial heterogeneity in case increase probabilities, with Coblong, Arcamanik, and Antapani exhibiting the highest long-term risk. A strong correlation (R² = 0.9473) was found between case increase probabilities and projected insurance benefits and premiums. The practical implication of this study lies in its provision of a data-driven framework that enables insurance companies to align policy pricing with region-specific and evolving pandemic risks, including long-term health consequences such as post-COVID-19 conditions. This approach enhances both the fairness of premium structures and the financial resilience of insurers in managing future public health crises.
Co-Authors Azis, Rheznandya Arkaputra DELIMA, ANGGUN CITRA Dian Anggraini Dianpermatasari, Aprilia Dzakiya, Azizah Edriani, Tiara Shofi Edy Soewono Eka, M Eldhyawati, Silmie Yashifa Fatimah, Syifa Nurul Gres Maretta, Gres Hamidi, Muhammad Rozzaq Huda, Nur'ainul Miftahul Imro'ah, Nurfitri Indratno, Sapto Wahyu Irfanullah, Asrul Mufidah, Zunanik Mukhaiyar, Riki Nadwah, Hamidah Qurrotun Novi Mardiana Nulhakim, Imam Nuraziza Arfan Puspita, Dila Puspito, Antonius Nanang T. Rifky Fauzi Rizka, Nela Saefudin Saefudin Sari, Febrina Puspa Sri Haryani Styaningrum, Amalia Suherlan, Bagas Caesar Syam, Husnul Khatimah Utami, Riani Widyani, Sasqia Bunga Zainnuddin, Ahmad Fuad