Pemodelan Statistik Total Klaim BPJS Kesehatan Berbasis Distribusi Pareto dan Weibull: Pendekatan Non-Homogeneous Poisson Process
Abstract
BPJS Kesehatan must be prepared with adequate financial reserves to pay participant claims, which requires careful financial analysis and management. One aspect of this analysis is estimating claim inter-arrival times and claim amounts using data patterns from various hospital types (A, B, C, and D). Given the time-varying intensity of claims, the Non-Homogeneous Poisson Process is the suitable method for this study. The best distribution models were selected based on the smallest Kolmogorov-Smirnov value. The findings indicate the best model for inter-arrival time data is a Pareto distribution, with different parameters for each hospital type. For claim amounts, the analysis shows claims from type A and D hospitals follow a three-parameter Weibull distribution, while claims from type B and C hospitals follow a two-parameter Weibull. Based on these results, BPJS Kesehatan needs to prepare average monthly reserve funds of IDR 10–11 trillion, with extreme scenarios requiring up to IDR 11–12 trillion per month.
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DOI: https://doi.org/10.37905/euler.v13i2.33562
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