Selamat Datang Di Repository Universitas Royal

Lamhot Jaya Motor is a financing company that provides cash loan services with motor vehicle BPKB guarantees. However, the selection process for prospective customers which is still carried out manually causes delays in decision making, increases the risk of bad debts, and reduces operational efficiency. Therefore, this study applies the K-Means Clustering method to group prospective customers based on creditworthiness. This study involves the stages of data collection, data processing, application of the K-Means algorithm, and implementation of a Visual Basic and MySQL-based system. The results of the study show that the developed system is able to classify customers into three categories: very creditworthy, creditworthy, and not creditworthy. Thus, the application of the K-Means Clustering method to this system can improve the accuracy of credit analysis and accelerate the decision-making process at Lamhot Jaya Motor.


Keywords: K-Means Clustering; Credit Worthiness; Data Mining; Visual Basic; MySQL