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All Journal Jurnal Varian
Wakhidah, Melani Nur
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

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PENERAPAN ANN DAN GARCH PADA ANALISIS VOLATILITAS PERAMALAN TINGKAT KLAIM BIAYA RAWAT INAP TINGKAT PERTAMA (RITP) BPJS KESEHATAN Pahrany, Andi Daniah; Wakhidah, Melani Nur; Norrulashikin, Siti Mariam Binti
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.5422

Abstract

The volatility of First-Level Inpatient Care (RITP) claim costs poses a substantial challenge to BPJS Health’s financial management, underscoring the need for accurate forecasting methods. This study employs Artificial Neural Network and Generalized Autoregressive Conditional Heteroscedasticity models to examine volatility dynamics and assess predictive performance. The results indicate that both models capture nonlinear patterns, heteroskedasticity, and temporal dependencies, with evidence that past fluctuations largely influence current volatility. Forecast accuracy is generally high, as reflected in the small discrepancies between predicted and actual values across most provinces. Nevertheless, the models exhibit limitations in capturing extreme peaks and troughs, where abrupt claim variations are not fully represented. These findings highlight the effectiveness of Artificial Neural Networks and Generalized Autoregressive Conditional Heteroscedasticity in modeling claim volatility, while emphasizing the need for model refinement, such as parameter optimization or integration with complementary approaches, to enhance forecasting reliability. 
Co-Authors Andi Daniah Pahrany Norrulashikin, Siti Mariam Binti