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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Referensi Islamika: Jurnal Studi Islam
Atilla Aslanargun
Eskisehir Technical University
Religion Humanities Computer Science & IT

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The Best K-Exponential Moving Average with Missing Values: Gold Prices in Indonesia, Saudi Arabia, and Turkey during COVID-19 Fadhlul Mubarak; Atilla Aslanargun; Ilyas Siklar
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2021 No. 1 (2021): Proceedings of 2021 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2021i1.42

Abstract

There have been missing values in the gold price data for Indonesia, Saudi Arabia, and Turkey at the weekend so that imputation techniques have been carried out to solve this problem. The imputation method of replacing NAs with the latest non-NA values also known as last observation carried forward (LOCF) made it a solution to overcome the missing values. This study selected the best -exponential moving average based on the smallest mean absolute percentage error (MAPE) from simulations. The 2-exponential moving average analysis was the best analysis for the price of gold which has missing values in Indonesia, Saudi Arabia, and Turkey during COVID-19, while the largest MAPE values are different for each country.
BEST FORECASTING FOR THE CAPITAL ADEQUACY RATIO OF THE FINANCIAL PERFORMANCE OF ISLAMIC COMMERCIAL BANKS IN INDONESIA Vinny Yuliani Sundara; Nurniswah; Fadhlul Mubarak; Atilla Aslanargun
Referensi Islamika: Jurnal Studi Islam Vol. 4 No. 3 (2026): JUNI
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/ri.v4i3.526

Abstract

This study aims to determine the best forecasting method for CAR by comparing three approaches, namely automatic autoregressive integrated moving average (auto-ARIMA), multilayer perceptron (MLP) neural networks, and ensemble method and to see their relationship to resilience, prudence, public trust, and stability of Islamic banking institutions. The CAR data used is monthly time series data published by the Financial Services Authority (OJK) in Indonesia for the period 2015-2025. Training and testing data are used to evaluate forecasting performance using mean absolute error (MAE), mean squared error (MSE), and mean absolute percentage error (MAPE). Forecasting results using the auto-ARIMA (0,1,0) model, the best method, confirmed that CAR is on a stable and sustainable path. This finding reinforces CAR's role as a multidimensional indicator linking financial performance, institutional resilience, sharia compliance, prudence, and social responsibility of Islamic banks to the community. The accuracy of this forecasting has direct implications for strengthening Islamic banking governance by increasing capital resilience in the face of future economic shocks. The ability to accurately predict CAR allows management to prioritize prudent principles in financing distribution, thereby mitigating the risk of systemic failure. Furthermore, well-planned capital ratio stability will strengthen public confidence in the security of funds in Islamic financial institutions. Reliable CAR forecasting not only supports managerial decision-making, but also contributes to strengthening the stability and credibility of Islamic banking as an institution responsible for society and the economy in Indonesia.
Co-Authors Fadhlul Mubarak Fadhlul Mubarak Ilyas Siklar Nurniswah Vinny Yuliani Sundara