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Analysis Of the Effect of Internal Performance on Bank Profitability Tri Basuki, Agus; Rahman, Arif
International Journal of Social Science, Education, Communication and Economics Vol. 3 No. 1 (2024): April
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sj.v3i1.294

Abstract

This study aims to determine the effect of CAR, LDR, NPL, BOPO, and Bank Size. This study uses quantitative methods and panel data regression models to investigate how internal factors or bank ratios affect the profitability of KBMI 3 and 4 banks in Indonesia. The research sample consisted of 8 KBMI banks 3 and 4 using Purposive Sampling covering the 2015-2022 period. The estimation method in the selected panel data is the Fixed Effect Model approach. The results of this study show that the profitability of Bank KBMI 3 and 4, as measured by ROA, partially LDR variables have a significant positive influence, BOPO and Asset Size have a significant negative influence, CAR and NPL do not have a significant and negative effect, while simultaneously have a significant influence. The findings of this study provide empirical evidence regarding the effect of financial ratio variables or internal bank factors on the profitability of Bank KBMI 3 and 4, which in turn can be useful for policy makers, academics, and investors.
Analysis of Commercial Bank Performance Dynamics Based on KBMI1–KBMI4 Using a Panel ECM Approach Tri Basuki, Agus
International Journal of Science, Technology & Management Vol. 7 No. 3 (2026): May 2026
Publisher : Publisher Cv. Inara Colaboration with www.stie-sampit.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v7i3.1427

Abstract

This study aims to analyze the performance dynamics of commercial banks in Indonesia based on KBMI1, KBMI2, KBMI3, and KBMI4 groups using a dynamic panel Error Correction Model (ECM) approach. The data used consist of monthly panel data covering the period from June 2025 to January 2026. The ECM model is employed to examine both short-term and long-term relationships among variables affecting bank performance, while also capturing the adjustment process toward long-run equilibrium. The results indicate that there is a long-run equilibrium relationship between the variables studied and bank performance across all KBMI groups. The Error Correction Term (ECT), which is significant and negatively signed, suggests that when short-term disequilibrium occurs, the system will adjust back toward long-term equilibrium. This finding implies that the model used is appropriate in capturing the adjustment dynamics of banking performance. In the short run, several variables exhibit varying effects on bank performance across KBMI groups. These differences in responses reflect heterogeneity in behavior among bank groups, where banks in higher KBMI categories tend to demonstrate greater stability compared to those in lower KBMI groups. Furthermore, the estimation results show that the dynamic panel model with the ECM approach is capable of explaining variations in bank performance reasonably well, making it relevant for analyzing the banking sector. Overall, this study concludes that the performance of commercial banks in Indonesia is influenced not only by short-term factors but also significantly determined by long-term equilibrium relationships. The ECM approach proves to be effective in capturing these dynamics, particularly in distinguishing characteristics across KBMI groups.
Key Drivers of Digital Transformation among MSMEs in Kulon Progo Regency Yantoro, Yuli; Ma'ruf, Ahmad; Tri Basuki, Agus
JURNAL MANAJEMEN MOTIVASI Vol 22 No 1 (2026): Jurnal Manajemen Motivasi
Publisher : Universitas Muhammadiyah Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29406/jmm.v22i1.8762

Abstract

Digital transformation remains context-specific for MSMEs, especially in non-metropolitan regions. This study examines its drivers among MSMEs in Kulon Progo Regency, Indonesia, using an exploratory qualitative design and MICMAC analysis of expert judgments from practitioners, academics, and government. Twenty variables were mapped through influence–dependence analysis. Results indicate that external forces customer digital demand, competitive pressure, digital infrastructure, ecosystem conditions, and cybersecurity concerns are primary drivers. Organizational and institutional factors function mainly as relays, while internal capabilities appear as outcomes. The findings highlight policy priorities to strengthen external enablers and intermediary mechanisms for sustainable regional MSME digitalization.