The COVID-19 pandemic that is spreading in Indonesia has affected economic growth, likewise banks sector. This study aims to determine the financial performance factors that are affected by the COVID-19 pandemic, both in Islamic and conventional banking which are included in the CBGB 2 category so that banks in Indonesia can anticipate it. This study uses the Artificial Neural Network (ANN) method with 6 financial performance variables in the period of January 2020 - September 2020, namely Capital Adequacy Ratio (%), Operating Expenses / Operating Income (%), Net Operation Margin (%), Landing on Deposits. Ratio (%), Short Term Mismatch (%) which are used as the independent variable, as well as Return on Assets which is used as the dependent variable. The results showed that the COVID-19 pandemic affected financial performance factors in the form of a Funding to Deposit Ratio of 35.21%; Short Term Mismatch of 26.92% and Net Operation Margin of 26.92% in Islamic banking. Whereas in conventional banking, Operating Expenses to Operating Income was 72.87% and the Capital Adequacy Ratio was 17.31%. This result is also in line with previous research where Islamic banking is more vulnerable than conventional banking in facing financial crises.

Islamic banking fall on stagnation of financial performance in 2011 after successfully overcoming the financial crisis in 1998 and 2008, as though the Islamic banking sector had only run in place and had no clear purpose in developing the Islamic finance business. The purpose of this study is to clarify the variables that predispose financial performance, as well as predict the decrease and increase of financial performance. This study uses an Artificial Neural Network (ANN) model to find out the variables that affect financial performance and predict the decrease and increase of financial performance of sharia and conventional banking for the next five months. This research generates the variables which affect the financial performance of sharia banking and the prediction of financial performance over the next five months. The variables which affect the level of financial performance of sharia banking affected dominantly by inflation, although the results of conventional banking are the same but not too significant. This shows that sharia banking CBGB (Commercial Bank – Group of Business) 2 is very vulnerable with macroeconomic factors compared with conventional banking. ANN predictions produce an average of 80% success in predicting performance over the next five months, this result is consistent with previous research.

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Purpose – The purpose of this study was to determine the extent of the impact of Covid-19 on the macroeconomic indicators and financial performance of Islamic banks in Indonesia. The results of this study may serve as a reference for the Indonesian government and Islamic banks’ stakeholders in formulating strategic decisions in creating innovative solutions during the Covid-19 pandemic.Methodology – Quantitative research method with 2 approaches, namely Partial Least Square-Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN) was selected for this study.Findings – This study demonstrated that macroeconomic indicators were significantly affected by the Covid-19 pandemic. However, the results of the ANN and PLS-SEM models varied. The PLS-SEM model illustrated the impact of the Covid-19 pandemic affecting the performance of Islamic banking, while the ANN model did not.Implication – This research has implications for stakeholders, especially the government to maintain macroeconomic stability, while for Islamic banking management to focus more on product innovation and service excellence so that it can be closer to the public, especially Muslims community.Originality – Numerous studies examining macroeconomics and the financial performance of Islamic banking have been conducted. This study aimed to offer an alternative perspective by using two models, namely PLS-SEM and ANN.

Purpose – This study aims to optimize the role of mosques in increasing economic welfare and reducing widespread public usury loans. Moreover, this study also aims to determine the right model for Islamic financial activities.Methodology – This is a qualitative study and the Analytic Network Process (ANP) BOCR model was utilized to obtain the ideal model according to literature reviews and expert opinion. This study conducted in-depth interviews with 5 experts (Ulama, Regulators (Financial Services Authority), Fintech Practitioners, fintech academics, and the Indonesian Mosque Council).Findings – Three alternative models were chosen by the experts, namely the Crowdfunding Model (0.47), Peer-to-Peer landing (0.37), and Bank Infaq (0.17). In addition, the experts suggested for attention to be made to the cost factor (0.47) so as not to burden the mosque. Moreover, according to the experts, the benefits (0.28) that will be obtained will be greater for the welfare of the mosque and residents around the mosque if fintech crowdfunding is implemented.Originality – Research on the role of mosques in improving people's welfare by utilizing fintech is very rarely done. The results of this study are expected to increase the role of the community in collecting funds and controlling the distribution of tabarru' funds.Research limitations – This type of research is exploratory, and empirical research is needed for in-depth results.Practical implications – If this research is implemented, it will accelerate the recovery of economic conditions during a crisis.Social implications – The successful implementation of the Islamic Social Finance (ISF) model by utilizing the role of the mosque will improve the welfare of the community evenly.