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Odi Isya Winanda
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PREDIKSI RATING FILM ANIMASI BERDASARKAN ELEMEN MISE EN SCENE MENGGUNAKAN NEURAL NETWORK Odi Isya Winanda; Selly Artaty Zega; Raihan Hilmawan
JOURNAL OF APPLIED MULTIMEDIA AND NETWORKING Vol 3 No 1 (2019): Journal of Applied Multimedia and Networking
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.737 KB) | DOI: 10.30871/jamn.v3i1.1427

Abstract

A production house can make adjustments in releasing the film if knows the possibility of success to the related film. The goal is to get maximum profit after thefilm is released. It can even use a prediction to know how market developmentsare. In this study, the authors used data from IMDb to predict the rating on a film.Because IMDb is the largest database consisting of relevant and comprehensiveinformation related to films. It is necessary to consider the additional features ofvisual, which basically refers to everything that appears on the screen. Everythingcaptured by the camera consisting of settings, lighting, the human figure, andcomposition, these four elements are part of the mise en scene. To determine thelevel of accuracy in film rating predictions, the author uses the science of softcomputing, namely the neural network, focusing on the prediction part. Theaccuracy of the animated movie rating prediction is based on the mise en sceneelement which is equal to 44%, the accuracy is based on the average of each testoption.
Co-Authors Raihan Hilmawan Selly Artaty Zega