Asih Oktaviani
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Analisis Pengaruh Tingkat Suku Bunga Dan Pendapatan Terhadap Penyaluran Kredit Pada Pt Bank Pengkreditan Rakyat Piala Makmur Asih Oktaviani; Mexano Hans Gery; Agusman Agusman
Jurnal Point Equilibrium Manajemen dan Akuntansi Vol. 4 No. 2 (2022): Jurnal Point Equilibrium Manajemen dan Akuntansi
Publisher : Universitas Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59963/jpema.v4i2.239

Abstract

The interest rate is the amount of interest determined by the bank for credit loans to customers. The bank's main income comes from the credit distribution process which is inseparable from the risk of increasing the interest rate set. Therefore, to increase interest rates on lending, banks will use various methods, because changes in interest rates will affect the amount of credit disbursed and will also affect income. This research aims to determine the influence of interest rates and income on the amount of credit disbursement partially on the amount of credit disbursement at PT BPR Piala Makmur Sungai Geringging for the 2017-2021 period. The independent variables used in this research are interest rates and income, while the dependent variable is the amount of credit disbursement. The population used in this research is the annual financial reports for the 2017-2021 period, with a sampling technique using the saturated sampling method (Census). The data analysis technique used is quantitative descriptive analysis and multiple regression analysis then hypothesis testing using SPSS 25. The research results show that partially the interest rate (X1) has a significant negative effect on the amount of credit disbursement, Income (X2) has no effect and is not significant on the amount credit distribution. And for simultaneous influence, interest rates and income have a simultaneous (together) influence on credit distribution. From the regression results, the R-Square (R2) value is 0.688. This means that the independent variable is able to explain 68.8% of the dependent variable while the remaining 31.2% is explained by other variables.