Health Information Analysis of Bank OCBC NISP 2015 - 2019

Aims: Examine the health information of OCBC NISP banks between the relationship of ratio data finance ROA (Return on Assets) between the relationship ROA, NPL, LDR and BOPO data. Study Design: Statistical methods using the dependent variable is ROA (Return on Assets) and the independent variables namely NPL (Non-Performance Loan), LDR (Loan to Deposit Ratio), and BOPO (Operating Expenditures Operation Income) Data as health information analyzes Quarterly Data from 2015-2019 Place and Duration of Study: Information Systems, Faculty of Engineering, University Widyatama The research was Carried out between October 2019 to January 2020. Methodology: Collecting the data in this study tries to analyze information between related the data relationships of NPL (Non-Performance Loan), LDR (Loan Deposit Ratio), and BOPO (Operating Expenditures Operation Income) to ROA (Return on Assets) on the bank OCBC NISP in the period 2015-2019 and using the fixed effects method. Results: The results of this study NPL positive effect on ROA significant with a p-value of 0.6997, the coefficient NPL = +0.0536262, so any increase is in NPL 1% then the the resulting rise in ROA of 0.0536262%. For LDR positive effect on ROA and very significant with a p-value of 0.4301, the coefficient NPL = +0.00210031, so any increase is in NPL 1% then the the resulting rise of Case Study Mulyadi and Virgana; AJRCOS, 5(2): 17-24, 2020; Article no.AJRCOS.55219 18 0.00210031% ROA, and vice versa. To BOPO negative effect on ROA significant with a p-value of 0.0002, the coefficient of BOPO = -0.0793051, so any increase is in ROA of 1% then result in a Decrease of 0.0793051% ROA and vice versa. Conclusion: The correlation between the independent ROA relationship to the NPL, LDR and ROA is related to the bank's health analysis from the coefficient value shown on the R-squared value of 0.980778 to describe a set of independent variables and the dependent variable explained by 98%.