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This Author published in this journals
All Journal Perspectives in Mathematics and Applications (PERMATA) International Journal of Computing Science and Applied Mathematics-IJCSAM
Wahri Irawan
Universitas Islam Negeri Sultan Maulana Hasanuddin Banten
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Physics

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Truncated Gamma-Truncated Lomax Distribution in Modelling Data Claims Irmatul Hasanah; Wahri Irawan; Ikin Ainul Yakin
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 10 No. 2 (2024)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v10i2.4574

Abstract

One of the methods to analyze the risk of loss on insurance companies based on the historical data on claim payments is modelling the data into severity distribution. This research deals with severity distribution by connecting two distribution Truncated Gamma and Truncated Lomax in modelling claim payments. The Kolmogorov-Smirnov test is used to test the fit of model. The result shows that Truncated Gamma-Truncated Lomax distribution is the best model to analyze the risk of loss based on data claim payments. The AIC value of 1533,915 and the BIC value of 1550,132.
Penentuan nilai risiko sebagai ambang batas klaim asuransi kendaraan bermotor menggunakan distribusi gamma. Ardiyan Budiman; Wahri Irawan; Mochamad Indrajit Roy
Perspectives in Mathematics and Applications Vol 2 No 01 (2026): Juni
Publisher : Kreasi Pustaka Mandiri (Krestama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66256/permata.v2i1.47

Abstract

The growth of motor vehicles in Indonesia has increased the risk of traffic accident losses, highlighting the need for accurate claim risk management by insurance companies. One approach to determining claim thresholds is Value-at-Risk (VaR). This study aims to estimate VaR as a claim threshold for motor vehicle insurance by modeling claim amounts using the Gamma distribution. The research methodology includes descriptive analysis of claim data, distribution selection, parameter estimation via maximum likelihood, and goodness-of-fit testing with the Kolmogorov–Smirnov test. The data consist of 113 paid claim amounts from motor vehicle insurance during the 2024–2025 period. The results indicate that the claim data are positive and right-skewed, making them suitable for modeling with a Gamma distribution with shape parameter α = 10.9073 and scale parameter θ = 0.5457. The calculated VaR values are 30.8716 at the 95% confidence level and 36.687 respectively levels.
Co-Authors Ardiyan Budiman Ikin Ainul Yakin Irmatul Hasanah Mochamad Indrajit Roy