INFORMATION SYSTEM MODEL FOR DIGITAL MOVIE STORE USING RECOMMENDER SYSTEM

• Main Author: Kemal Pasha Hidayat , Mohammad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/8648
• Institution: Institut Teknologi Bandung

Advancements in information technology have affected business and culture, including music and film business and culture. Internet and audio/video compression technology have made piracy grows faster and easier, and now the whole industry is facing a decline. On the other hand, this condition has also given opportunities for the information technology to offer solutions in the forms of new technologies and new business models. The business models should enable movies to be sold and marketed more efficiently and easily, and there should be more places for people to buy movies. Information technology also enables films to be marketed with the use of Recommender System, a system which can recommendate products uniquely to each individuals according to their own preferences. The system makes it possible for movies to be marketed efficiently to the right people so that the increase of sales can be expected. This thesis analyse and design the development of digital film selling system which includes the Recommender System. Zachman Frameworks is used to analyse the architecture enterprise of the required system. The study shows how such system is possible to build and that Recommender System can improve sales, although the studies should be continued after the implementation phase. The use of Zachman Frameworks has given directions to link between the business requirements and system information planning, although the lack of methodology and standards has made the process to be done in unstructured steps. To be used in an industry where the planning process and mechanisms has to be defined in details, Zachman Frameworks should be combined with available methodologies to meet the industrys standards and best practices. The algorithm of the Recommender System made in this thesis has not met the desireable optimum permformance and hence need an improvement.It should be noted that the use of Recommender System in a store system would require some system resources that has to be considered.