Muhammad Hakim Sitompul
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REGULATORY DEVELOPMENTS IN SHARIA BANKING: IMPLICATIONS FOR THE DYNAMICS OF SHARIA BUSINESS UNIT SPIN-OFF IN INDONESIA Muhammad Hakim Sitompul
Journal on Islamic Economics, Finance & Banking [Z-CONOMICS] Vol. 1 No. 1 (2025): Journal on Islamic Economics, Finance & Banking [Z-CONOMICS]
Publisher : Az-Zahra Media Society

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Abstract

This research examines the impact of regulatory developments on the dynamics of Sharia Business Unit (SBU) spin-offs in Indonesia. The study aims to explore how regulatory frameworks, particularly Law No. 21 of 2008, influence the performance, compliance, and competitiveness of SBUs transitioning into independent Sharia Commercial Banks (SCBs). The scope of this research covers the financial, regulatory, and operational aspects of Islamic banking. A mixed-methods approach was employed, utilizing qualitative analysis of regulatory frameworks and quantitative financial data from various Sharia banks and SBUs. Data were sourced from financial reports and interviews with key stakeholders in the banking sector. The findings reveal that while spin-offs offer opportunities for SBUs to enhance market power and Sharia compliance, they also face challenges in governance and resource management. Notably, effective regulatory oversight and strategic management are crucial for long-term success. These results provide insights for policymakers and industry stakeholders on improving Islamic banking's competitiveness and sustainability.
ARIMA MODELS IN PREDICTING INDONESIAN ISLAMIC BANK PROFITABILITY Muhammad Hakim Sitompul; T. Rizkan Polem; Dede Ruslan; Muhammad Fitri Rahmadana
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 4 No. 4 (2024): August
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijebas.v4i4.1817

Abstract

This study aims to predict the profitability of Bank Muamalat Indonesia, proxied by the ROA ratio. The data analysis used is ARIMA (Autoregressive Integrated Moving Average), which is an appropriate approach for analyzing time series data such as the profitability of Bank Muamalat Indonesia over the period 2010-2023. The findings indicate that the ARIMA (1,1,12) model is the best in predicting the profitability of Bank Muamalat Indonesia. This is because the ARIMA (1,1,2) model demonstrates white noise characteristics and produces low AIC and SC values as well as significant parameters, thus it is selected for analysis. Using the ARIMA (1,1,2) model, profitability estimation shows RMSE values of 0.39 and MAE values of 0.32, indicating a low error rate. The prediction shows a significant decline in the profitability of Bank Muamalat Indonesia, although fluctuations remain. Therefore, the ARIMA (1,1,2) model proves to be effective in predicting the profitability of Bank Muamalat Indonesia with a low error rate, despite the prediction results showing a downward trend.