RENANO, REZA (2023) IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK MENENTUKAN ITEMSET TEMA ANIME PADA MYANIMELIST.NET. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This study uses FP-Growth algorithm to analyze the preferences and trends of anime viewers on Myanimelist.net. The analysis found that 'Edit Opening Theme' is the most frequently occurring itemset in the dataset, with support 0.144444, followed by 'Theme: School' with support 0.111111, and 'Themes: Gore, Military, Survival' with support 0.066666. These findings provide insight into the anime themes that are most popular among the platform's audience. In addition, this research has the potential to provide anime recommendations that match users' preferences, improve the platform's recommendation features, and support the development and marketing of new anime titles that match fans' interests. As such, this research provides practical benefits to the anime industry and fans, as well as providing a deeper understanding of anime audience trends on Myanimelist.net. Keyword : Anime, FP-Growth,Itemsets, Myanimelist.net Penelitian ini menggunakan algoritma FP-Growth untuk menganalisis preferensi dan tren penonton anime di Myanimelist.net. Hasil analisis menemukan bahwa 'Edit Opening Theme' adalah itemset yang paling sering muncul dalam dataset, dengan support 0.144444, diikuti oleh 'Theme: School' dengan support 0.111111, dan 'Themes: Gore, Military, Survival' dengan support 0.066666. Temuan ini memberikan wawasan mengenai tema anime yang paling populer di kalangan penonton platform tersebut. Selain itu, penelitian ini memiliki potensi untuk memberikan rekomendasi anime yang sesuai dengan preferensi pengguna, meningkatkan fitur rekomendasi platform, dan mendukung pengembangan dan pemasaran judul-judul anime baru yang sesuai dengan minat penggemar. Dengan demikian, penelitian ini memberikan manfaat praktis bagi industri anime dan penggemar, serta memberikan pemahaman yang lebih mendalam tentang tren penonton anime di Myanimelist.net. Kata Kunci : Anime, FP-Growth,Itemsets, Myanimelist.net
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 23 126 |
| Call Number: | SIK/15/23/070 |
| NIM/NIDN Creators: | 41519010098 |
| Uncontrolled Keywords: | Anime, FP-Growth,Itemsets, Myanimelist.net |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | Sekar Mutiara |
| Date Deposited: | 06 Oct 2023 03:08 |
| Last Modified: | 06 Oct 2023 03:08 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/81212 |
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