Jurnal Tekinkom (Teknik Informasi dan Komputer)
Vol 6 No 2 (2023)

ANALISIS PREDIKSI GENRE FILM PADA INTERNET MOVIE DATABASE INDONESIA MENGGUNAKAN METODE LONG SHORT TERM MEMORY

Dwi Novi Marito Tampubolon (Universitas Prima Indonesia)
Valentina Vincensia Hulu (Universitas Prima Indonesia)
Ryan Oktavianus Sipahutar (Universitas Prima Indonesia)
Oloan Sihombing (Universitas Prima Indonesia)



Article Info

Publish Date
23 Dec 2023

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.

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Journal Info

Abbrev

Tekinkom

Publisher

Subject

Computer Science & IT

Description

Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem ...