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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah KOMPUTASI JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JISICOM (Journal of Information System, Infomatics and Computing) Aisyah Journal of Informatics and Electrical Engineering Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) JURNAL POLI-TEKNOLOGI Knowbase : International Journal of Knowledge in Database Jurnal Kecerdasan Buatan dan Teknologi Informasi
Rakhmi Khalida
Universitas Bhayangkara Jakarta Raya
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

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OPTIMALISASI SISTEM REKOMENDASI PENYEWAAN TRUK MENGGUNAKAN CONTENT BASED FILTERING Aida Fitriyani; Rakhmi Khalida; Hendarman Lubis
Journal of Information System, Informatics and Computing Vol 10 No 1 (2026): JISICOM (June 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v10i1.2452

Abstract

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
Co-Authors Aida Fitriyani Dwi Hendarman Lubis Hudi Kusuma Bharata Khairunnisa Fadhilla Ramdhania Mayadi Mayadi R Wisnu Prio Pamungkas R Wisnu Prio Pamungkas Siti Setiawati Situmorang Tubagus Maulana Kusuma