Classification of Rental Vehicle Units at Permata Transindo Sidoarjo Car Rental Using K-Means Clustering Algorithm
Pengelompokkan Unit Kendaraan Sewa Pada Rental Mobil Permata Transindo Sidoarjo Menggunakan Algoritma K-Means Clustering
DOI:
https://doi.org/10.21070/ups.7420Keywords:
K-Means Clustering, Rental CarAbstract
This research focuses on grouping rental vehicle units at Permata Transindo Sidoarjo Car Rental using the K-Means Clustering algorithm. The increasing need for efficient transportation services makes car rental a practical solution. However, companies face challenges in managing their fleet and providing suitable unit recommendations. This study aims to analyze the popularity of vehicle units based on collected rental data. The K-Means Clustering method was used, allowing data grouping based on similar characteristics. The results showed that four optimal clusters were identified, with the lowest Davies-Bouldin Index (DBI) of 0.834135. Each cluster represents a unit category based on rental duration and budget. This provides valuable insights for companies in managing their vehicle fleet effectively and providing unit recommendations that suit customer needs. This study emphasizes the importance of implementing the K-Means method as a tool in decision-making in the car rental industry.
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