ANALISIS DAN VISUALISASI DATA KREDIT MENGGUNAKAN METODE EXPLORATORY DATA ANALYSIS PADA LPD UMANYAR
Abstract
This study aims to analyze and visualize credit data of the Village Credit Institution (LPD) of Umanyar Traditional Village using the Exploratory Data Analysis (EDA) approach. The study addresses the issue of high principal and interest arrears observed during the period 2020–2024. A total of 1,150 credit records were processed through data preprocessing stages, including data cleaning, handling missing values, data type conversion, and category adjustment. The EDA results reveal patterns and relationships between loan tenure, interest rates, debtor characteristics, and delinquency levels. Longer loan tenures were found to be associated with higher delinquency risk, while male debtors exhibited higher delinquency rates compared to female debtors. In addition, non-performing loans were concentrated in certain regions, indicating the influence of local economic conditions. These findings demonstrate that EDA is effective in identifying credit risk patterns and provides valuable insights to support the formulation of more targeted credit policies and risk mitigation strategies at the LPD of Umanyar Traditional Village.
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