PREDICTING MOVIE BOX OFFICE REVENUE USING ARTIFICIAL NEURAL NETWORK
The film industry has grown immensely over the past few decades generating billions of dollars of revenue for the stakeholders, however, the cost needed to create a movie is very high, so it becomes a tremendous challenge for the production companies to produce movies that are highly successful a...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/49383 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The film industry has grown immensely over the past few decades generating
billions of dollars of revenue for the stakeholders, however, the cost needed to
create a movie is very high, so it becomes a tremendous challenge for the
production companies to produce movies that are highly successful and generates
high revenue called blockbuster or a movie with the revenue bigger than
$100.000.000. The competitive advantage the production companies currently
have is the current advancement in technology, which if they are able to fully take
advantage of it, they will be able to reduce the chance of producing failed movies.
In this paper, artificial neural network is chosen as a method to predict the success
of the box office movie. The ability of the artificial neural network method in
making predictions certainly needs to be supported by determining the important
variables that will be used in the construction of the model. In this paper, the
author uses the chi squared test method for determining important variables of
categorical input data and categorical output data and the ANOVA method for
determining important variables of numerical input data and categorical output
data. As a result, the authors managed to get an accuracy of 86% in the test set,
which means that 86% of the test data can be classified correctly. |
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