Optimization Analysis Model Determining PNMP Mandiri Loan Status
Based on Pearson Correlation

Optimization Analysis Model Determining PNMP Mandiri Loan Status
Based on Pearson Correlation

Classification Analysis, Loan Status, PNPM Mandiri, Artificial Neural Networks, Person Correlation

PNPM Mandiri is an organization engaged in financing small and medium enterprises in the community. The problem that
always occurs is an error in determining the loan status resulting in bad credit. This study aims to present a classification
analysis model for determining loan status at PNPM Mandiri. The classification analysis model was built using the Perceptron
algorithm artificial neural network. The analysis model will later be optimized using the Person Correlation (PC) method to
measure the accuracy of the variables used. The research dataset is based on historical data from the last 2 years as many as
67 data samples. The analysis variables consist of Business Type (X1), Loan Amount (X2), Collateral (X3), Income (X4), and
Expenses (X5). The results of the analysis show that the model built can provide optimal classification results. These results
can be seen based on the results of variable measurements using the PC method indicating that variable X2 has no significant
relationship. With the results of these measurements, the performance of the artificial neural network presents maximum results
in determining loan status. Overall, the results of this study can provide an effective analytical model as well as an alternative
solution for determining loan status.

Teri Ade Putra1
, Pradani Ayu Widya Purnama2
, Riandana Afira3
, Yesri Elva4

Universitas Putra Indonesia YPTK Padang

29-12-2022

Fajar Bagus W

PDF

Indonesia

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