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All Journal Specta Journal of Technology Jurnal Forum Analisis Statistik Jurnal Pendidikan dan Sosial Humaniora
Eli Zulkatri
Institut Teknologi Kalimantan
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science

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Journal : specta journal of technology

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Indonesian Mortality-Based Dual Purpose Life Insurance Premium Model with Multiple Decrement and Interest Rate Sensitivity Aris Pransisco Siringo Ringo; Eli Zulkatri; Ahmad Rhandy Irsandha; Brayen Endo Raldie; Novia Ramadhany Rumengan; Natalie Mawar Desember Desember; Beby Griselda Putri
SPECTA Journal of Technology Vol. 10 No. 1 (2026): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v10i1.8481947

Abstract

Endowment life insurance is a product that provides benefits both upon the insured's death and while they remain alive until the end of the contract period. Determining premiums for this product requires a model that can capture multiple types of risk, making the multiple-decrement approach relevant. This study aims to calculate dual-purpose life insurance premiums by considering two causes of termination, namely death and inability to pay (lapse), using Indonesia's TMI 2023 mortality data, the probability of default from the OJK 2025 report, and interest rate sensitivity scenarios. The research methods include compiling life expectancy and active-payment probability tables, determining discount factors based on a deterministic interest rate model across three scenarios (pessimistic, realistic, optimistic), and calculating the present value of benefits and annual premiums for two decrement cases. The results show that premiums are highly sensitive to interest rates. Lower interest rates result in higher premiums, while higher interest rates reduce premiums according to the discount principle. In Case 1 (death) and Case 2 (default), different premium values are obtained due to variations in the decrement probabilities of each risk. Overall, the multiple decrement model proved to provide more accurate calculation results that are in line with the actual risk conditions in Indonesia. This study also identified potential developments by incorporating a stochastic interest rate model and adding other types of decrements to support more comprehensive premium setting for the insurance industry.
Designing a Revenue Blueprint for JKN: A Hybrid Time-Series and AI Forecasting Approach: 257 - 268 Nadya Haryanto; Aura Nabil Arsy; Mila Fitria Sari; Ahmad Tijani Noor; Eli Zulkatri
SPECTA Journal of Technology Vol. 10 No. 2 (2026): Specta Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v10i2.8481933

Abstract

Indonesia’s National Health Insurance (JKN) system faces significant sustainability challenges driven by regional economic heterogeneity and fluctuating payment compliance, particularly within the informal sector. Traditional linear forecasting models often fail to capture the complex, nonlinear interactions between revenue and broader macroeconomic drivers. This study aims to propose a Hybrid Time Series-AI framework for monthly JKN contribution revenue forecasting to enhance financial resilience. The methodology employs an additive decomposition approach, integrating Autoregressive Integrated Moving Average (ARIMA) to capture linear trends and Long Short-Term Memory (LSTM) networks to model nonlinear residuals and exogenous variables. The research utilizes a spatially enriched dataset (2020–2025) incorporating national macroeconomics and regional indicators such as provincial minimum wages (UMP) and Gross Regional Domestic Product (GRDP). Results reveal that JKN revenue is highly elastic to UMP (r > 0.8) and regional economic stability. The hybrid model, validated through rolling forecasts, yielded a Weighted Absolute Percentage Error (WAPE) of 45.18% during the volatile 2024 period, effectively capturing structural shocks that standard models overlook. These findings are translated into a “Blueprint Revenue JKN Masa Depan,” providing BPJS Kesehatan with a granular tool for adaptive liquidity buffering, region-specific risk management, and long-term fiscal planning.
Co-Authors Ahmad Rhandy Irsandha Ahmad Tijani Noor Alvianus Kristian Sumual Aris Pransisco Siringo Ringo Aura Nabil Arsy Beby Griselda Putri Brayen Endo Raldie Jacline Indriany Sumual Lili Hernawati Mila Fitria Sari Nadya Haryanto Natalie Mawar Desember Desember Novia Ramadhany Rumengan Putri Amalia Yumna Aqila Zainul Muttaqin