Skripsi : SISTEM REKOMENDASI FILM INDONESIA MENGGUNAKAN ALGORITMA APRIORI - Baperan | Ragam Berita Terkini | Beritanya Bikin Baper

Skripsi : SISTEM REKOMENDASI FILM INDONESIA MENGGUNAKAN ALGORITMA APRIORI

10 January 2015

The development computing and communication has produced the thirst for information (Witten, et al. 2011).  As well as the use of technology computer in various fields such as economics, science and social life an number of digital data that is very big (Perner, 2002).  Digital data can be in the form that will be stored text, images, video and audio, where a group data is stored in a database systems. A rapid growth and integration of database system resources has extensive to the researchers that aims to analyze scientific data, optimizing industrial system, and found a pattern that valuable information in the database was (Hand, et al. 2001).  So much information that is still hidden in the database, which was very important information but not yet found in or not in diction Kan (Witten, et al. 2011).  Therefore, there needs to be a technique in processing information that valuable and useful in data collection. In a simple data mining is a technique for extraction or "mined" knowledge from a group that the amount of data (Han, et al. 2006).

In the world film industry, data processing is also not less important.Especially in this study authors involving data from national film. Quantity film production national experiencing an increase dramatically, from only 6 film at the end of 1949 to 22 films in the year 1950 and 58 films in the year 1955 (Junaedi, 2009).  With the number of films that more and more each year, it made audiences difficulty in finding and choose film which is the right time to be seen (Tsalaatsa, et al. 2013), especially for national film that information is quite small. It required a system that has function to display a recommendation film based on certain variables.

The recommendations are a software and techniques to give a suggestion recommendations for items that will be used by the users and aims to help in the various decision-making processes, such as if what to purchase, music what must be heard or news what they want to read, (Ricci, et al. 2011).  Recommendation system development has been implemented in various fields, one of them is or Animal Quarantine (2011) that make recommendations tourism system using a Hybrid nearest neighbor, where there is no such research in tourism.

In application context recommendations, the use of the term data mining is describing collection analysis techniques used to conclude or draw a conclusion a policy recommendations or build models recommendations from data that a group of (Schafer, 2009).  Many technical data mining or algorithm that can be used for research system recommendations. There have been many also or that use techniques data mining, such as Aritonang (2012) with the research data Mining implementation of the Association Rule In decision-making In Correlation Will products Using Logarithm Priory, Adyatma (2013) with the research Using Data Mining In decision-making System acceptance New Employees With the method Decission Tree And C4.5.

In this research I'm going to use algorithm Priory in defining the terms an associative between variables such as frequency ratings and genres of preferences for users to produce a recommendation to film the users.

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