ALFANSYURI, MUHAMMAD VALENSYAH (2022) IMPLEMENTASI SISTEM REKOMENDASI DENGAN METODE CONTENT-BASED FILTERING MENGGUNAKAN ALGORITMA APRIORI PADA WEBSITE LELANG IKAN HIAS. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The ornamental fish auction business in Indonesia is a business that is well known to the public. Ornamental fish auction transactions can now be found via WhatsApp, Instagram, or Facebook. With the large number of ornamental fish hobbyists, one of the media that can help transaction activities is to use platforms such as websites. To make it easier for hobbyists to find their favorite fish, one way that can be done is to implement a recommendation system on the ornamental fish auction website with the content-based method using the a priori algorithm. Based on user activity data on the website, you can find product categories to recommend with a support value of more than 75% and a confident value of 125%. By category Betta → Reptile/Amphibian association. It can be concluded that if the user performs an activity on the Betta product, the Reptile/Amphibian products will also perform the same activity. The results of this algorithm can help provide product recommendations to users of ornamental fish auction websites or other platforms who want to implement a recommendation system. Key words: Algoritma apriori, Association rule, Content-based filtering, Lelang ikan hias Bisnis lelang ikan hias di Indonesia merupakan salah satu bisnis yang sudah umum diketahui masyarakat. Transaksi lelang ikan hias kini sudah dapat ditemui melalui media Whatsapp Instagram, ataupun Facebook. Dengan banyaknya jumlah penghobi ikan hias maka salah satu media yang dapat membantu kegiatan transaksi adalah dengan menggunakan platform seperti website. Untuk memudahkan penghobi dalam menemukan ikan favoritnya maka salah satu cara yang dapat dilakukan adalah dengan implementasi sistem rekomendasi pada website lelang ikan hias dengan metode content-based menggunakan algoritma apriori. Berdasarkan data aktivitas user pada website dapat ditemukan kategori produk untuk direkomendasi dengan nilai support lebih dari 75% dan nilai confident mencapai 125%. Dengan asosiasi kategori Cupang → Reptil/Amfibi. Hal ini dapat disimpulkan jika user melakukan suatu aktivitas pada produk cupang, maka aktivitas yang sama juga akan dilakukan para produk Reptil/Amfibi. Hasil dari algoritma ini dapat membantu untuk memberikan rekomendasi produk kepada pengguna website lelang ikan hias ataupun platform lain yang ingin menerapkan sistem rekomendasi. Kata kunci: Algoritma apriori, Association rule, Content-based filtering, Lelang ikan hias
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 22 003 |
| NIM/NIDN Creators: | 41518010126 |
| Uncontrolled Keywords: | Algoritma apriori, Association rule, Content-based filtering, Lelang ikan hias |
| 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 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | Dede Muksin Lubis |
| Date Deposited: | 09 Jun 2022 07:08 |
| Last Modified: | 09 Jun 2022 07:08 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/63012 |
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