Investigating the effect of total assets, financing, and third-party funds on Islamic Banking Revenue in Indonesia

2020 ◽  
Vol 18 (2) ◽  
pp. 85-94
Author(s):  
Rani Salamah Marinda ◽  
Imam Asngari ◽  
Mukhlis Mukhlis
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Financial Services ◽  
Secondary Data ◽  
Multiple Regression Model ◽  
Quantitative Approach ◽  
Third Party ◽  
Islamic Banking ◽  
Study Analysis

This study investigates the influence of total assets, total financing, and third-party funds on the revenue of Islamic banking in Indonesia. Data used are secondary data during the period 2005-2018 sourced from the Financial Services Authority (OJK). The study analysis used a quantitative approach by applying the multiple regression model estimated by OLS. The findings of the study indicated that total assets and third-party funds has a positive and significant effect, while the financing has a negative and significant effect on Islamic banking revenue in Indonesia during the analysis period

scholarly journals DANA PIHAK KETIGA DAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA PADA PERBANKAN SYARIAH DI INDONESIA

2013 ◽  
Vol 2 (2) ◽  
Author(s):  
Dewi Sartika
Keyword(s):  
Exchange Rate ◽  
Gross Domestic Product ◽  
Regression Model ◽  
Statistical Method ◽  
Financial Statements ◽  
Multiple Regression Model ◽  
Third Party ◽  
Domestic Product ◽  
Islamic Banking ◽  
The Exchange Rate

This study examines the effect of GDP (Gross Domestic Product) and the exchange rate on U.S. dollar against the TPF (Third Party Funds) in Indonesia. The objective of Islamic banking in this study was to analyze the influence of GDP (Gross Domestic Product) Rupiah rate against U.S. dollar deposits (Fund Party Third) of Islamic banking in Indonesia. In writing this makes the GDP (Gross Domestic Product) and the rupiah rate to U.S. dollar as the variables that influence to measure how much influence on Deposits (Third Party Funds). This study used 24 samples comprising the financial statements starting from January 2004 till December 2009. The method used in this study is the statistical method with a multiple regression model, where to find or measure how much influence given by the GDP (Gross Domestic Product) and exchange rate on U.S. dollar against the TPF (Third Party Funds) Islamic banking. The result showed that the variables GDP (Gross Domestic Product) and the exchange rate on U.S. dollar deposits have a significant effect on the Fund (Third Party) Islamic banking in IndonesiaDOI: 10.15408/sjie.v2i2.2426

scholarly journals The Effect Of Third Party Funds (DPK), Non Performing Financing (NPF), And Indonesian Sharia Bank Certificates (SBIS) On Sharia Banking Financing Distribution In Indonesia

2021 ◽  
Vol 2 (2) ◽  
pp. 72-77
Author(s):  
Riyan Pradesyah ◽  
Yuyun Triandhini
Keyword(s):  
Data Analysis ◽  
Commercial Bank ◽  
Financial Services ◽  
Quantitative Methods ◽  
Secondary Data ◽  
Third Party ◽  
Islamic Banking ◽  
Analysis Technique ◽  
Negative Effect ◽  
Positive Effect

The purpose of this research is to determine the effect of DPK, NPF, and SBIS either partially or simultaneously on the distribution of Islamic banking financing in Indonesia. In this research , using quantitative methods and the type of data used is secondary data. The sample used in this study is data on total financing, DPK, NPF and fund placement in Islamic Commercial Bank SBIS which are contained in the monthly Islamic Banking Statistics published by the Financial Services Authority for the period 2015 - 2019. The data analysis technique used in this study is test classical assumption, multiple linear regression and hypothesis testing. The results of this study were processed in the SPSS 22 program.The results showed that partially (t test) the DPK variable had a positive effect on the distribution of financing. This was evidenced by the t count (56.185)> (1.67252) t table and the sig value. 0.000 < 0.005. The NPF variable has a negative effect with t count (-3.914) <(1.67252) t table and sig. 0.000 < 0.005. The SBIS variable has no effect, as evidenced by the t count (1.536) <(1.67252) t table and the sig value. 0.130 > 0.005. Taken together (F test) shows that DPK, NPF, and SBIS have a significant effect on financing distribution as evidenced by the value of F count (1565,122)> (2.77) F table and sig. 0.000 < 0.005. The adjusted R2 value is 0.988, which means that the DPK, NPF and SBIS variables affect the distribution of financing by 98.8% while the remaining 1.2% is influenced by variables outside of this research .

scholarly journals PENGARUH JUMLAH ZAKAT PRODUKTIF, UMUR PRODUKTIF, JUMLAH TANGGUNGAN, DAN PENGAWASAN TERHADAP PRODUKTIVITAS USAHA (SURVEY PADA MUSTAHIK KABUPATEN PIDIE)

2020 ◽  
Vol 5 (2) ◽  
pp. 288-296
Author(s):  
Assafriani Assafriani ◽  
Meutia Fitri
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Secondary Data ◽  
Multiple Regression Model ◽  
Information Collection ◽  
Independent Variable ◽  
Variable Influence ◽  
And Control

This study aims to determine the influence of   productive zakat amount, productive age, dependents of mustahik, and controll towards  productivity of mustahik reaching. This research is conducted by taking samples of mustahik who earn productive zakat from Baitul Mal Pidie and chosen sample for 53 mustahik. The data and information collection used in this study was documentation technique. The data used was the secondary data which directly collected from Baitul Mal Pidie. The testing of independent variable influence toward the dependent variabel used this study was multiple regression model by using SPSS 23.The result of the reseach shows that simultaneously productive zakat amount,productive age, dependents of mustahik, and control have an effect productivity of mustahik reaching.   However partially only variable productive zakat amount and controll that effect the productivity of mustahik reaching. Productive age and dependents of mustahik are not affect the productivity of mustahik reaching

scholarly journals Determinant of Market Share in the Indonesian Islamic Banking Industry

2021 ◽  
Vol 12 (1) ◽  
pp. 1-16
Author(s):  
Syafiq Mahmadah Hanafi
Keyword(s):  
Market Share ◽  
Financial Services ◽  
Banking Industry ◽  
Secondary Data ◽  
Third Party ◽  
Islamic Banking ◽  
Determinant Factors ◽  
Automated Teller Machines ◽  
Banking Market

Market share determines the position of revenue and public utilization of Sharia bank. This research aims to examine the internal and external determinant factors of Indonesia Sharia banking market share. The secondary data were obtained from the Financial Services Authority (OJK) and Bank Indonesia (BI). Autoregressive Distributive Lag (ARDL) was used to explore the short and long periods from the influence of variables, including total of offices, customers, third-party saving (DPK), and promotion. The results showed that the total number of Automated Teller Machines (ATM) had a contrastingly different impact. Therefore, this research recommends adding all variables quantitatively.

Factors Affecting NPAs in Indian Banking Sector

Paradigm ◽  
2021 ◽  
Vol 25 (2) ◽  
pp. 181-193
Author(s):  
Nitya Garg
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Banking Sector ◽  
Relative Weight ◽  
Multiple Regression Model ◽  
Factors Affecting ◽  
Weight Analysis ◽  
Specific Factors ◽  
Relative Weight Analysis ◽  
Bank Specific Factors

Banking sector is the backbone of any economy, so it is necessary to focus on its performance which is largely affected by its non-performing assets (NPAs). In the year 2018–2019, NPA of scheduled banks was Rs 355,076 Crore which is 3.7% of net advances. The purpose of this study is to identify the determinants based on analysis from previous literatures, and majorly macroeconomic and bank specific factors which are affecting NPAs using the relative weight analysis and to frame a model to predict future NPAs using multiple regression model using SPSS. The study also attempts to focus on actions and remedies that banks should make to control future NPAs. Findings of the study will act as a scaffolding for financial analysts and policymakers to prevent the conversion of its performing assets into NPAs and also help in proper management of banks and also in the recovery of economy.

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