OPTIMALISASI SISTEM REKOMENDASI PENYEWAAN TRUK MENGGUNAKAN CONTENT BASED FILTERING - Aida Fitriyani; Rakhmi Khalida; Hendarman Lubis (Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta, 2026)
In general, people do not have information in choosing the type of truck based on the load requirements and the type of goods to be transported when renting a truck. The high risk of accidents usually occurs due to overcapacity, vehicle mismatch with needs. Precisely determining the type of logistics fleet can now be accommodated through a web-based recommendation system equipped with a direct booking module. Through this platform, users can specify vehicles specifically based on load parameters, such as weight capacity and commodity category. In its development, the Waterfall methodology was systematically applied, encompassing the stages of needs analysis, system design, program code writing, testing, and periodic maintenance. The accuracy of this system was evaluated using the Cosine Similarity algorithm . Based on the trial results, the system successfully produced a very high level of recommendation similarity, with a coefficient value reaching 0.9487. The implementation of this technology has proven to be able to optimize the accuracy of fleet selection, reduce rental process time, and minimize security risks during the logistics distribution process