Evaluation Indonesian Financial Performance of Islamic Commercial Bank using Gaussian Mixture Model with Intervention Analysis - Syalsabilla, Alya Fitri; Astutik, Suci; Shahuneeza Naseer, Mariyam (IKONOMIKA, 2024)
Indonesia, with its rich diversity and sizable Muslim population, holds a prominent position in global Islamic finance. Financial ratios like ROA, CAR, NPF, FDR, BOPO, and NOM are crucial for assessing bank performance. Employing Gaussian Mixture Model with Intervention Analysis enhances evaluation by identifying outliers and understanding their impact.Utilizing Islamic Banking Statistics from January to December 2023, this research employs purposive sampling to select relevant variables like CAR, NPF, FDR, BOPO, NOM, and ROA. Gaussian Mixture Model identifies data patterns, while Intervention Analysis examines factors affecting Islamic banking performance.Financial performance analysis reveals shifts from "Good Performance" to "Bad Performance" starting June 2023, linked to deteriorating metrics like NPF, FDR, and BOPO. Evaluation via GMM yields an AIC of 435.3409, indicating effective classification. Intervention analysis identifies significant NPF and ROA outliers, suggesting potential issues in loan quality and profitability.Analysis via GMM highlights performance dynamics in Islamic commercial banks, transitioning from "Good" to "Bad" post-June, mirroring critical metric shifts. Stable CAR indicates a solid base, but NPF outliers suggest risk management enhancements. BOPO outliers indicate inefficiencies, while ROA emphasizes profitability. Policy interventions should focus on risk management, cost efficiency, and profitability to sustain stability and competitiveness.