Analisis Preferensi Pengguna terhadap Genre Film Menggunakan Eksplorasi Data pada Dataset MovieLens
Keywords:
data science, exploratory data analysis, movie genres, movielens, user preferencesAbstract
This study aims to explore user preferences for movie genres based on rating behavior in the MovieLens dataset during the period of 2023 to 2024. Using exploratory data analysis (EDA) techniques, this research examines the distribution of ratings, genre popularity in terms of average and total ratings, and behavior of the most active users. The results of the study indicate that Drama, Action, and Comedy are the most frequently watched and rated genres by users in the MovieLens dataset. However, genres such as Film-Noir, War, and Western have the highest average ratings, despite having relatively fewer ratings. These findings suggest that user preferences are influenced not only by the popularity of genres but also by the satisfaction level with films in those genres. Furthermore, analysis of the most active users reveals variations in individual preferences, which can serve as a foundation for developing more personalized and accurate recommendation systems.


