Model Sistem Pendukung Keputusan Kelayakan Pemberian Kredit Pada BUMDes

Decision-making for granting credit to BUMDes XYZ customers, which is still done manually,
allows the results of decisions taken to be subjective, resulting in inaccurate decision results.
This inaccurate credit decision has the potential to increase the number of bad loans that occur.
This article presents a Decision Support System (DSS) model for assessing creditworthiness
using the Simple Additive Weighting (SAW) method, with reference to the 5C criteria (Character,
Capacity, Capital, Collateral and Condition). The performance accuracy of the SAW method
was tested with 30 samples of bad credit data and current loans of customers of a BUMDes in
Bali, using the Confusion Matrix technique. The test results show the Precision value of 95.4%
and recall of 91.3%. The accuracy value is classified as Excellent Classification based on the
ROC (Receiver Operating Characteristic) curve. The final result of the SAW-based SPK model
is then implemented in the form of an SPK application for providing credit to BUMDes XYZ
customers.