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All Journal EKSAKTA: Journal of Sciences and Data Analysis Media Statistika Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Science and Technology Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) International Journal of Supply Chain Management Jurnal Matematika UNAND Journal of Fundamental Mathematics and Applications (JFMA) Journal of Research Applications in Community Services Eduvest - Journal of Universal Studies Indonesian Journal of Mathematics and Applications Indonesian Actuarial Journal
Adhitya Ronnie Effendie, Adhitya Ronnie
Departemen Matematika, FMIPA, Universitas Gadjah Mada
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Probabilistic Earthquake Hazard Assessment in Indonesia Using Poisson Model and Spatial Grid Analysis Hartati; Effendie, Adhitya Ronnie; Susyanto, Nanang; Suryanto, Wiwit
Science and Technology Indonesia Vol. 11 No. 1 (2026): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.1.207-216

Abstract

Indonesia, located at the convergence of three major tectonic plates in the Pacific Ring of Fire (ROF), is highly susceptible to earthquakes. This study analyzes earthquake hazard in Indonesia using a statistical approach based on the Poisson distribution combined with spatial mapping through a 0.5o x 0.5o grid. Earthquake  data from the USGS catalog (1925–2025), including time, location, depth, and magnitude, were analyzed. Annual earthquake frequencies were calculated for each grid cell with magnitude ≥ 5.0, and the probability of at least one event occurring within 10, 25, and 50 years was estimated using the Poisson probability function. Results were visualized as spatial probability risk maps for 10-, 25-, and 50-year horizons, enabling the identification of earthquake-prone areas and classification of risk levels. The findings reveal that subduction zones, particularly along the Sunda Arc, exhibit probabilities exceeding 90% for M≥ 5 events within the next 50 years, highlighting their significance for disaster preparedness. These results demonstrate that a Poisson-based statistical and spatial approach is effective for probabilistic earthquake hazard mapping and provides direct support for disaster risk reduction and spatial planning in Indonesia.
A Deeper Look Into an Insurance Risk Model with Two Types of Claims and FGM Copula Dependency Saruan , Sandy Salomo; Effendie, Adhitya Ronnie
Indonesian Actuarial Journal Vol. 1 No. 2 (2025): Indonesian Actuarial Journal
Publisher : Persatuan Aktuaris Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65689/iajvol01no2pp095-112

Abstract

This paper investigates a continuous-time, two types of claims risk model where the dependence between claim sizes and inter-claim times is structured using a Farlie–Gumbel–Morgenstern (FGM) copula. The methodology begins with the construction of a Lundberg’s equation and the determination of its non-negative roots. Subsequently, the integro-differential equation for the ruin probability is derived, from which the Laplace transform of the ruin probability is obtained. For the specific case of exponentially distributed claim sizes, an explicit analytical expression for the ruin probability is derived to examine the effects of dependence parameters and distributional characteristics. A series of numerical experiments with varying FGM copula parameters demonstrate that the ruin probability decreases as the initial surplus increases and is significantly influenced by the strength of the dependence structure. From a practical perspective, distinguishing between claim types allows insurers to identify which category poses the greatest threat to solvency, thereby supporting more targeted underwriting and accurate capital allocation strategies.
From Risk-Neutral to Risk-Sensitive Reinforcement Learning: Actor–Critic vs REINFORCE with Tail-Based Risk Measures Lestia, Aprida Siska; Effendie, Adhitya Ronnie; Tantrawan, Made; Azrarsyah, Muhammad Rafli
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40309

Abstract

his study investigates the application of \emph{risk-sensitive reinforcement learning} on heavy-tailed return series by comparing two primary algorithms: REINFORCE with baseline (REINFORCE-BL) and episodic batched actor--critic (A2C-B). Initial exploratory analysis reveals an asymmetric return distribution with numerous extreme \emph{outliers}, rendering variance-based risk measures inadequate and motivating the integration of tail-based risk measures—specifically Value at Risk (VaR), Conditional Value at Risk (CVaR), and Entropic Value at Risk (EVaR)—into the RL objective function. This study constructs a simple portfolio environment with discrete actions (market entry, market exit, and \emph{hold}) and trains both algorithms under four scenarios: risk-neutral, VaR, CVaR, and EVaR. Experimental results demonstrate that A2C-B consistently outperforms REINFORCE-BL across all scenarios, exhibiting higher average long-term rewards, faster convergence rates, and more stable \emph{learning curves}. While VaR and CVaR penalties significantly reduce rewards and increase learning volatility for REINFORCE-BL, A2C-B experiences only moderate reward reductions while maintaining stability. In the EVaR scenario, both algorithms yield high rewards, yet A2C-B retains a slight advantage in terms of stability. These findings indicate that in environments with heavy-tailed returns, employing coherent risk measures (particularly CVaR and EVaR) within an actor--critic framework offers a more compelling trade-off between tail risk control and average performance, serving as a viable \emph{baseline} for the development of risk-sensitive RL in finance and actuarial science.
Co-Authors A'yun, Qonita Qurrota Abdul Talib Bon Abdurakhman Abdurakhman Abdurakhman Abdurakhman Alsitaningtyas, Yunike Jemis Fifnelavindy Anaviroh Anaviroh Azrarsyah, Muhammad Rafli Danardono Danardono Danardono, Danardono Dani, Andrea Tri Rian Dedi Rosadi Devni Prima Sari Faihatuz Zuhairoh Fidia Deny Tisna Amijaya Hardina Sandariria HARTATI indarsih, Indarsih Indradewa, Rhian Kariyam - Kariyam Kariyam Lestia, Aprida Siska Muhammad Iqbal Al-Banna Ismail Muhammad, Hubbi Mulyadi, Taqriri Kamal Putra, Fachrian Bimantoro Rohmatul Fajriyah Sandelvia, Krismona Saruan , Sandy Salomo Selvi Faristasari Sifriyani, Sifriyani Solikhatun, Solikhatun Sri Haryatmi Kartiko Sri Wahyuni Sukono Sukono Suryanto, Wiwit Susyanto, Nanang Syaripuddin Syaripuddin Tantrawan, Made Uha Isnaini Utami, Rianti Siswi Wahyujati, Mohamad Fahruli Yotenka, Rahmadi Yuciana Wilandari Yuciana Wilandari Yulianti, Silvina Rosita Yulita, Tiara