TIME SERIES PREDICTION ON MOVIE RATING DATA

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dc.contributor.authorLaksana, Eka Angga
dc.contributor.authorMurnawan
dc.date.accessioned2021-02-08T05:18:14Z
dc.date.available2021-02-08T05:18:14Z
dc.date.issued2020
dc.description.abstractTime series is known as method to make prediction based on series of data. It has some benefit in a lot of research domain including marketing, sport and education area. Movie is popular entertainment part which has a great number of fans. People choose movie with specific genre and has share some similar interest. This research use Movielens dataset as input for time series processing. This dataset contains historical data about user, ratings and datetime. This research implements timeseries on the Movielens dataset to make prediction on rating value by using fbprophet library. The experiment shows that the algorithm can predict the future rating which approximately will be chosen by users. Then the objective of this research is to create recommendation based on predicted rating for whatever movie on the next choice.en_US
dc.identifier.issn1475-7192
dc.identifier.urihttp://repository.widyatama.ac.id/xmlui/handle/123456789/12210
dc.language.isoenen_US
dc.publisherInternational Journal of Psychosocial Rehabilitation, Vol.24, Issue 02en_US
dc.subjectTime Seriesen_US
dc.subjectMovieen_US
dc.subjectRatingsen_US
dc.subjectMovielensen_US
dc.subjectFbpropheten_US
dc.titleTIME SERIES PREDICTION ON MOVIE RATING DATAen_US
dc.typeArticleen_US
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