Pencarian Produk E-Commerce Berdasarkan Judul Dan Deskripsi Menggunakan Vector Space Model

Pencarian Produk E-Commerce Berdasarkan Judul Dan Deskripsi Menggunakan Vector Space Model

• By Ayuni, Asistyasari;
• Jurnal Nasional Tidak Terakreditasi
• 338
• 52-57

E-Commerce in Indonesia has increased every year, especially B2C sales and this is directly proportional to the increasing number of e-commerce sites in Indonesia. One of the things that this site offers is the ease of finding the product you want to find. However, in several tests conducted, it turns out that some Indonesian e-commerce sites are unable to search for products based on the description keyword. Therefore, the author tries to do this research using the VSM algorithm and produces an accuracy of 60%, a precision of 72.73% and a recall of 80%..

• Katakunci E-Commerce, Vector Space Model, Text Mining, CRISP-DM
• URL http://ejournal.ibm.ac.id/jurnal-komti-computer-information-system-technology-vol-1-des-2020/
• Penerbit ,

REFERENSI

Aprilla, D, Baskoro, Donny Aji, Ambarwati, Lia, & Wicaksana, IWayan Simri. (2013). Belajar Data Mining dengan Rapid Miner. Jakarta.

Irmawati, 2017. Sistem Temu Kembali Informasi Pada Dokumen Dengan Metode Vector Space Model. Jurnal Ilmiah FIFO. Vol IX, No. 1

Kusrini & Luthfi, 2009. Algoritma Data Mining. Andi Offset, Yogyakarta.

Larose, Daniel, 2005. Discovering Knowledge in Data : An Introduction to Data Mining. John Willey & Sons. Inc.

Leman, D., Andesa, K., 2015. Implementasi Vector Space Model Untuk Meningkatkan Kualitas Pada Sistem Pencarian Buku Perpustakan. Seminar Nasional Informatika. Vol 1, No. 1. Medan.

Prasetya Chandra Saha Dewa, 2017. Sistem Rekomendasi Pada E-Commerce Menggunakan K-Nearest Neighbor. Jurnal Teknologi Informasi dan Ilmu Komputer. Vol. 4, No. 3

Sawant, Uma, Gabale & Subramanian. 2017. E-fashion Product Discovery Via Deep Text Parsing. International Word Web Conference Committee. Australia.