UIN (Universitas Islam Negeri) Sunan Kalijaga, Yogyakarta: E-Journal Fakultas Ekonomi dan Bisnis Islam
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The Role of Profit-Sharing Ratio, Sharia Financial Market Securities, and Covid-19 in Influencing Third Party Funds of Islamic Banking in Indonesia
Full text linkThis study aims to analyze the influence of Profit Sharing Ratio (Nisbah), Sharia Money Market Securities (SBPU Syariah), and the Covid-19 pandemic on Islamic banking Third Party Funds (DPK) in Indonesia. The data used is a monthly time series secondary data from January 2018 to December 2023 consisting of 72 observations, obtained from OJK Sharia Banking Statistics. The analysis methods used were multiple linear regression and quadratic functional form regression with the application of STATA. The results of the study show that the variables of Profit Sharing Ratio and Sharia Money Market Securities (SBPU Syariah) have a positive and significant effect on Third Party Funds. However, the relationship between the Ratio and the Third Party Funds is non-linear, where the increase in the ratio to a certain point encourages the growth of the Third Party Fund, but will decrease after passing the optimal point. Meanwhile, the Covid-19 dummy variable also has a positive and significant influence on Third-Party Funds, showing that during the pandemic people tend to increase their deposits in Islamic banking
Analisis Pengaruh Harga Minyak Dunia, Suku Bunga dan Nilai Tukar terhadap Inflasi di Indonesia Periode 2018–2024
Full text linkPenelitian ini bertujuan untuk menganalisis pengaruh harga minyak dunia, suku bunga, dan nilai tukar terhadap inflasi di Indonesia selama periode 2018–2024. Menggunakan data time series bulanan dan regresi linier serta kuadratik, ditemukan bahwa suku bunga berpengaruh signifikan secara non-linear terhadap inflasi, menunjukkan pola hubungan melengkung. Sebaliknya, nilai tukar dan harga minyak dunia tidak menunjukkan pengaruh signifikan. Variabel dummy COVID-19 memiliki dampak negatif signifikan terhadap inflasi. Model kuadratik memiliki daya jelas lebih tinggi dengan Adjusted R-squared sebesar 47,46%. Temuan ini memberikan implikasi penting bagi efektivitas kebijakan moneter dalam mengendalikan inflasi, terutama pada dinamika suku bunga
Analisis Pengaruh Fear of Missing Out dan Kepedulian Lingkungan terhadap Keputusan Investasi Hijau: Studi pada Generasi Z
Full text linkPenelitian ini bertujuan untuk menganalisis pengaruh Fear of Missing Out (FoMO), literasi keuangan syariah, dan sikap peduli lingkungan terhadap keputusan investasi hijau. Investasi hijau dipahami sebagai bentuk investasi yang tidak hanya berorientasi pada keuntungan finansial, namun juga memperhatikan aspek keberlanjutan lingkungan. Generasi Z, yang dikenal sebagai generasi digital dan peduli isu sosial, menjadi fokus penelitian ini karena memiliki potensi besar dalam mendorong praktik investasi berkelanjutan. Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei terhadap 155 responden Generasi Z. Teknik analisis yang digunakan adalah Partial Least Square–Structural Equation Modeling (PLS-SEM) dengan bantuan perangkat lunak SmartPLS 4. Hasil penelitian menunjukkan bahwa FoMO, literasi keuangan syariah, dan sikap peduli lingkungan berpengaruh positif dan signifikan terhadap keputusan investasi hijau. Temuan ini memperkuat teori Social Cognitive Theory yang menyatakan bahwa perilaku dipengaruhi oleh interaksi antara faktor personal, lingkungan sosial, dan kognitif. Penelitian ini memberikan kontribusi teoretis dalam memperluas kajian perilaku keuangan dan kontribusi praktis dalam merancang strategi edukasi dan promosi investasi hijau yang tepat sasara
The Role of Audit Quality in the Relationship between ESG and Corporate Financial Performance
Full text linkPurpose: The purpose of this study is to determine how environmental, social, and governance performance affects financial performance and how audit quality is able to moderate the relationship between environmental, social, governance performance and financial performance in companies listed on ISSI.
Methodology: The research method used is quantitative; the data in this study are secondary data accessed through the company\u27s official website in the form of annual financial reports and sustainability reports. Sampling using the purposive sampling method and obtained a sample of 52 samples. The processing of this research data uses the EViews 12 application.
Findings: The results of the study stated that environmental influences financial performance, social influences financial performance, independent board of commissioners influences financial performance, and audit committee influences financial performance. Institutional ownership influences financial performance. Audit quality as a moderating variable in the study can moderate the relationship between environmental and social factors and financial performance but failed to moderate the relationship between the independent board of commissioners, the audit committee, and institutional ownership and financial performance.
Novelty: In this study, only the social aspects of GRI were used to assess social variables. and the use of the audit quality variable as a moderating variable
AI-Enhanced Risk-Return Optimization in Islamic and Conventional Banking Portfolios
Full text linkPortfolio risk assessment in Islamic versus conventional banking requires advanced analytical approaches due to complex market dynamics and regulatory differences. Traditional optimization methods often fail to capture non-linear relationships and volatility patterns inherent in these distinct banking sectors. This study introduces an AI-enhanced framework combining Monte Carlo simulation with Solver-based optimization to compare market risks and determine optimal portfolio weights between Islamic and conventional banking stocks. The methodological innovation lies in integrating Microsoft Excel\u27s GRG nonlinear AI solver for real-time portfolio optimization, addressing limitations of conventional Markowitz models. Using 194 daily price observations from LQ45 and JII70 indices (January-October 2024), we analyzed four banking stocks (BRIS, BTPS, BBCA, BBRI) through Monte Carlo VaR simulation with 10,000 iterations and AI-driven optimization at 95% confidence level. Mann-Whitney tests confirmed significant differences between Islamic and conventional banking returns and risk profiles. Results reveal Islamic banking portfolios demonstrate significantly higher risk (VaR: -4.18%, potential loss: IDR 4,180,169) compared to conventional portfolios (VaR: -1.65%, potential loss: IDR 1,652,541). AI optimization yielded distinct allocation strategies: Islamic portfolio (45.4% BRIS, 54.5% BTPS) versus conventional portfolio (74.5% BBCA, 25.4% BBRI). This research provides the first AI-integrated comparative framework for Islamic-conventional banking risk analysis, offering quantitative evidence that challenges assumptions about Islamic banking stability. The study demonstrates practical applications of machine learning in portfolio management for emerging markets, providing actionable insights for different investor risk profiles while advancing methodological approaches in Islamic finance research
Navigating AI Integration in Islamic Enterprises: A Qualitative SWOT Perspective
Full text linkThis study explores the integration of Artificial Intelligence (AI) within Islamic strategic management frameworks using a qualitative SWOT analysis approach. The objective is to assess how AI can be ethically and effectively applied in Islamic enterprises, ensuring alignment with Shariah principles such as tawhid (the oneness of God), the balance between worldly and spiritual goals, and the pursuit of mardhatillah (divine pleasure). Using systematic literature review and SWOT framework, this research identifies internal strengths such as ethical leadership and community orientation and external opportunities such as the global halal market while addressing technological limitations and potential threats like ethical ambiguity and regulatory gaps. The findings highlight the importance of ethical leadership, community-based innovation, and strategic partnerships in navigating AI integration. This study contributes to the discourse on Shariah-compliant digital transformation and offers practical recommendations for AI governance rooted in Islamic values
Faktor-faktor Penentu Untuk Mencapai Peningkatan Pertumbuhan Ekonomi Di Indonesia
Full text linkPenelitian ini bertujuan untuk mengetahui pengaruh Indeks Produksi Industri (IPI), inflasi, kurs, dan perdagangan Internasional terhadap pertumbuhan ekonomi ndonesia dengan Penanaman Modal Asing (PMA) sebagai variabel intervening. Penelitian ini menggunakan pendekatan kuantitatif dengan data sekunder yang diambil dari website world bank. Data yang digunakan data time series dari tahun 1983-2022. Data yang diperoleh diolah dengan alat analisis Eviews 10. Uji yang digunakan untuk menguji hipotesis dengan uji stasioner, uji regresi, uji asumsi klasik dan uji path analysis. Berdasarkan hasil uji t menunjukkan hasil bahwa Indeks Produksi Industri (IPI) berpengaruh positif signifikan terhadap pertumbuhan ekonomi, inflasi berpengaruh positif signifikan terhadap pertumbuhan ekonomi, kurs berpengaruh negatif tidak signifikan terhadap pertumbuhan ekonomi, perdagangan internasional berpengaruh negatif signifikan terhadap pertumbuhan ekonomi, Penanaman Modal Asing (PMA) berpengaruh positif signifikan terhadap pertumbuhan ekonomi, Indeks Produksi Industri (IPI) berpengaruh positif signifikan terhadap Penanaman Modal Asing (PMA), inflasi berpengaruh positif tidak signifikan terhadap Penanaman Modal Asing (PMA), kurs berpengaruh positif tidak signifikan terhadap Penanaman Modal Asing (PMA), perdagangan internasional berpengaruh negatif tidak signifikan terhadap Penanaman Modal Asing (PMA), Indeks Produksi Industri (IPI) berpengaruh terhadap pertumbuhan ekonomi melalui Penanaman Modal Asing (PMA), dan variabel inflasi, kurs, dan perdagangan internasional tidak memiliki pengaruh terhadap pertumbuhan ekonomi melalui Penanaman Modal Asing (PMA)
Factors Affecting Peer-to-Peer (P2P) Lending Bad Debts in Java and Sumatra
Full text linkPurpose: This study aims to analyse the factors that influence bad debts in Peer-to-Peer (P2P) lending platforms in Jawa and Sumatra. The emergence of fintech as an alternative financing solution for the public and UMKM has created new challenges in the form of high credit risk. This study is motivated by the rapid growth of the fintech industry in Indonesia and the limited academic studies comparing credit risk based on geographical region.
Methodology: This study uses monthly time series secondary data for the period January 2021 – December 2024 obtained from the OJK Fintech Lending Statistics report. This study uses the Autoregressive Distributed Lag (ARDL) method to see the short-term and long-term effects of the variables of loan amount, loan purpose (individual and business entity), and male and female debtors.
Findings: The results showed that the amount of the loan did not have a significant effect on bad debts. Meanwhile, other variables have a significant effect on bad debts.
Novelty: This research has novelty in terms of region; the research focuses on two regions in Indonesia, namely Jawa and Sumatra. These two regions were chosen because they have different economic characteristics of infrastructure and access to financial services
Analisis Kemiskinan di Indonesia
Full text linkThe aim of this research is to analyze poverty factors in Indonesia. The data used is panel data with data from 34 provinces from 38 provinces in Indonesia. The type of data used is in the form of panel data, namely a combination of cross sections and time series over a period of 4 years 2019-2022. The method used is quantitative data consisting of the open unemployment rate, poverty rate and human development index. The research results showed that open unemployment rate had an insignificant positive effect on poverty levels and HDI could not moderate the effect of open unemployment levels on poverty in Indonesia
Artificial Intelligence and Islamic Finance: Enhancing Sharia Compliance and Social Impact in Banking 4.0
Full text linkResearch Aims: This research explores consumers’ perspectives on adopting artificial intelligence (AI) in Asian countries, focusing on its role in the banking sector.
Methodology: This quantitative research has distributed questionnaires to eleven Asian countries: Pakistan, China, Iran, Saudi Arabia, Indonesia, Malaysia, Bangladesh, Nepal, India, Afghanistan, and Thailand. The study received 550 usable responses, which provided valuable insights into consumer attitudes towards AI in banking.
Research Findings:The findings revealed that several factors, including responsiveness, perception of AI, individual perspective, perceived value, and comprehension of AI technology, significantly and positively impact AI adoption plans in the banking sector. However, risk perception exhibited a negative yet considerable relationship with adoption intentions.
Theoretical Contribution: This research is unique because it provides a better understanding of consumer perceptions of AI adoption in the banking sector in Asian countries. It offers a unique perspective on the strategic implications for banking management in leveraging AI technology for improved customer service and revenue generation, with a specific focus on the growing relevance of AI in Islamic finance.
Research limitation and implication: These implications are essential for strategic decision-making in the banking industry. The findings highlight the importance of building consumer trust and confidence in digital technology, enabling banks to overcome risks and enhance customer satisfaction. For Islamic financial institutions, these insights can guide the integration of AI in ways that align with Sharia principles, such as ensuring transparency, ethical data use, and risk-sharing mechanisms. This will not only improve operational efficiency but also strengthen the appeal of Islamic banking to tech-savvy consumers