The Analysis of Financial Banks in Libya and Their Role in Providing Liquidity - Saeeid Mohammad, Sami; Dian Wisika Prajanti, Sucihatiningsih; Setyadharma, Andryan (Universitas Negeri Semarang, 2020)
A commercial bank is a type of financial institution that accepts deposits, offers checking account services, makes various loans, and offers basic financial products like certificates of deposit (CD) and savings accounts to individuals and small businesses. Liquidity is the ability of banks to meet their debt obligations, can repay all depositors, and can meet credit requests submitted by debtors without a deferment. This shows that there are several factors and indicators that affect liquidity in banks in libya such as ROA, ROE, NPL, CAR and Bank Size. By analyzing commercial banks, it will be known the factors that most influence their liquidity. The aim of this research is to the analysis of financial banks in libya and their role in providing liquidity. This research will used quantitative research. Data collection method in this research is documentation with secondary data since year 2012-2019. The hypothesis test in this study is done by using Panel Regression analysis and ANOVA. Analysis results analysis of financial banks in libya and their role in providing liquidity is showed analysis compare common effect models with fixed effect models also Lagrange Multiplier Test the best estimation method is the Common Effect. R Square (R2) value is equal to 0.917. The magnitude of the R Square determination coefficient number is 0.917 or equal to 91.7%. This number means that the ROA, ROE, NPL, CAR, and SIZE variables together to influence the Providing Liquidity variables. While the remaining (100%-91.7% = 8.3%) are influenced by other variables outside this regression equation or variables not examined. The F test is 0.000, because sig. 0.000 < 0.05, then the basis of the providing liquidiy in the F test can be concluded that ROA, ROE, NPL, CAR, and SIZE have an effect on commercial bank in Libya, which means significant. Thus, the R coefficient value in the multiple linear regression analysis has been fulfilled. Based on the analysis data, the result showed that there analysis of financial banks in libya and their role in providing liquidity and influenced by other variables outside this regression equation or variables not examined. Suggestions for future research is to add another variables that analysis of financial commercial banks.