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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Ryan Oktavianus Sipahutar
Universitas Prima Indonesia
Computer Science & IT

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ANALISIS PREDIKSI GENRE FILM PADA INTERNET MOVIE DATABASE INDONESIA MENGGUNAKAN METODE LONG SHORT TERM MEMORY Dwi Novi Marito Tampubolon; Valentina Vincensia Hulu; Ryan Oktavianus Sipahutar; Oloan Sihombing
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.925

Abstract

A film producer is a person who initiates, coordinates, supervises, and manages the managerial and administrative aspects of film production. This research aims to predict the Film Genre in the Indonesian Internet Movie Database using the Long Short-Term Memory method to analyze the historical data of Indonesian film genres in the Internet Movie Database application for the previous 12 years. The research findings indicate that the LSTM algorithm model can generate accurate predictions with an RMSE value below 2.50 for both training and testing data, and it provides graphical results that can capture patterns and trends from the genre data of IMDb Movies Indonesia. The predictions in this study show that the drama genre has a higher predicted value to be released in the coming years.
Co-Authors Dwi Novi Marito Tampubolon Oloan Sihombing Valentina Vincensia Hulu