ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEDALAMAN JANGKAUAN (DEPTH OF OUTREACH) LEMBAGA KEUANGAN MIKRO (LKM) UED-SP DI KECAMATAN KUNTO DARUSSALAM KABUPATEN ROKAN HULU - Ahmad Rifai; Dita Putri Nitami; Roza Yulida (DINAMIKA PERTANIAN, 2017)
This research aims to (1) identify the range performance of Micro Financial Institutions (MFI) UED-SP in Kunto Darussalam sub-district Rokan Hulu district (2) Analyze factors affecting depth of outreach UED-SP MFI in Kunto Darussalam sub-district Rokan Hulu district. The type of data used in this research is secondary data derived from financial report of UED-SP MFI in Kunto Darussalam sub-district, Report of the Central Bureau of Statistics (CBS), Scientific journals and other institutions that support this research. The data analysis method used is descriptive statistical analysis and quantitative analysis by using analysis tool Econometrica data panel, where this research use software Eviews series 9. Through the Chow test and Hausman test, the panel data regression model used is fixed effect model (FEM). The result of data analysis shows that together (F-statistic test) the estimation result shows that the six independent variables ( Age of UED-SP MFI (AGE), return on asset (ROA), average values loan (AVL), capital asset ratio (CAR),amount of woman borrowers (POWB) and amount of trade sector borrowers (TRADE) ) have a significant effect on the variable average outstanding loan (AOL). Partially (t-statistic test), from the six independent variables used in this study, only two independent variables (age UED-SP MFI (AGE) and amount of trade sector borrowers (TRADE)) which has a significant effect on depth of outreach. Coefficient of determination test results (R2) Shows the value of R2 is equal to 0,9552 which means 95,52% depth of outreach variation can be explained by variation of age of UED-SP MFI (AGE), return on assets (ROA), average values loan (AVL), capital asset ratio (CAR), amount of woman borrowers (POWB), and amount of trade sector borrowers (TRADE). While the rest of 4,48 percent can be explained by other variables that are not included in the model.