IMPLEMENTASI SISTEM METASEARCH ENGINE E-COMMERCE DI INDONESIA MENGGUNAKAN PREFERENSI USER SEBAGAI

NIZAM, ABROR KHOERUN (2022) IMPLEMENTASI SISTEM METASEARCH ENGINE E-COMMERCE DI INDONESIA MENGGUNAKAN PREFERENSI USER SEBAGAI. S1 thesis, Universitas Mercu Buana Jakarta-Menteng.

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Abstract

E-commerce platform merupakan situs yang paling banyak dikunjungi di Indonesia. Total transaksi e-commerce di Indonesia tahun 2021 mencapai Rp 403 triliun. Untuk tetap menjaga tren positif kenaikan trafik pengunjung dan total transaksi yang luar biasa tersebut sistem e-commerce harus selalu berinovasi. Salah satu yang dapat dikembangkan yaitu dengan membuat fitur search relevan dengan preferensi user. Metasearch merupakan sistem pencarian yang berfungsi menampilkan hasil pencarian dari berbagai sumber pencarian. Semantic merupakan sistem pencarian yang menggunakan keterkaitan kata antar dokumen, semantic tidak hanya mencari berdasarkan kesamaan keyword pencarian. Penelitian menggunakan elasticsearch database dengan metode boosting query. Boosting query bertujuan untuk memberikan skoring lebih tinggi berdasarkan kesesuaian antara preferensi user dengan document yang diindex elasticsearch. Data preferensi yang diindex meliputi platform, jenis toko, harga barang. Dengan mendapatkan skor relevan maka document yang sesuai dengan preferensi user akan diutamakan dalam hasil pencarian. E-commerce platforms are the most visited sites in Indonesia. Total e-commerce transactions in Indonesia in 2021 will reach Rp 403 trillion. To maintain the positive trend of increasing visitor traffic and extraordinary total transactions, e-commerce systems must always innovate. One that can be developed is by making the search feature relevant to user preferences. Metasearch is a search system that displays search results from various search sources. Semantic is a search system that uses word linkages between documents, semantic does not only search based on the similarity of search keywords. The research uses an elasticsearch database with a boosting query method. Boosting query aims to provide a higher score based on the match between user preferences and the elasticsearch indexed document. Indexed preference data includes platform, type of store, price of goods. By getting a relevant score, documents that match user preferences will be prioritized in search results.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41517120003
Uncontrolled Keywords: E-commerce, metasearch, user preference, elasticsearch;
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 > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: Priyo Raharjo
Date Deposited: 06 Sep 2022 02:50
Last Modified: 06 Sep 2022 02:50
URI: http://repository.mercubuana.ac.id/id/eprint/68825

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