<![CDATA[The Indonesian logistics sector still faces operational efficiency challenges due to an unintegrated fleet management process and the dominance of manual recording. This situation makes it difficult for companies to objectively evaluate vehicle performance, especially in linking operational costs with achieved results. This research, a web based Fleet Management System, develops an efficiency analysis module using the Data Envelopment Analysis (DEA) model with a BCC (Variable Returns to Scale) orientation. The system is built with the Laravel framework, MySQL as a database, and Python integration to run on-demand DEA optimization based on the selected period and vehicle. The development method used is the Waterfall Software Development Life Cycle (SDLC), including needs analysis, design, implementation, and testing. The DEA variables consist of one input, the total operational cost of the vehicle, and two outputs, the distance traveled and revenue. Based on the analysis of 10 fleets (January–June 2025), the calculation results identify 4 fleets as relatively efficient and 6 fleets as inefficient, with a projected total estimated cost savings of Rp 75,918,125. Functional testing using Black-Box Testing showed that all key features ran with a 100% success rate, and the DEA algorithm on the validated system was highly accurate with a maximum difference of only 0.000043 compared to the MaxDEA software. This research resulted in an integrated platform that is able to improve the accuracy and speed of vehicle efficiency evaluation at PT. Fesa Antaran Logistik. In addition to providing practical benefits for the company, this system also offers an applicable DEA implementation model to support digitalization and data-driven decision-making in the logistics industry in Indonesia. Keywords: Data Envelopment Analysis, DEA BCC, Fleet Management System, Laravel, Python.]]>
