Sistem Rekomendasi Film Berdasarkan Profil Pengguna Menggunakan Metode Simple Additive Weighting Dan Pendekatan Ontologi

Abstract

Films are one of the most popular forms of entertainment, yet many people often struggle to find movies that match their preferences. To address this issue, this study aims to develop a movie recommendation system using the Simple Additive Weighting (SAW) method and an ontology-based approach to manage and organize complex information related to films. The study adopts the Design Science Research Methodology (DSRM) framework to identify key problems and design a solution that simplifies the process of selecting movies tailored to viewers' tastes.

The recommendation system was developed based on a thorough literature review and analysis of various factors influencing the movie-watching experience. By leveraging Methontology, an ontology was created to capture essential elements of movies, including genres, actors, directors, and other relevant attributes. The web-based system was built using Semantic Web technologies to ensure precise information retrieval through SPARQL queries, enabling accurate and relevant recommendations.

The system was tested with 30 users using the Black-box Testing method to validate its functionality comprehensively. Additionally, an evaluation using the Technology Acceptance Model (TAM) revealed positive feedback from users regarding ease of use, perceived benefits, and the accuracy of the recommendations provided. These findings demonstrate that the system is not only practical and effective but also holds significant potential to help users discover movies that match their preferences quickly and efficiently.