Rancang Bangun E-Commerce Menggunakan Collaborative Filtering Untuk Rekomendasi Produk Berbasis Framework Laravel

Auliasari, Rahma Evita and , Maryam , S.Kom., M.Eng (2026) Rancang Bangun E-Commerce Menggunakan Collaborative Filtering Untuk Rekomendasi Produk Berbasis Framework Laravel. Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

This research is motivated by the problem of MSMEs in krishna stores that still make transactions manually through notebooks, direct communication and social media such as WhatsApp. So that market reach is limited and sales are less than optimal. Therefore, a solution is needed in the form of an e- commerce website that can be an online transaction and is equipped with a product recommendation feature using the Item Based Collaborative Filtering method with Cosine Similarity calculation. This system is designed to expand market reach, improve user experience and support the competitiveness of MSMEs in the digital era. The system development uses the Software Development Life Cycle (SDLC) approach of the waterfall model, which includes the stages of needs analysis, design, implementation, testing, and maintenance. The technician's implementation is carried out with the laravel framework because it supports the Model-View-Controller (MVC) architecture, as well as the Mysql database to store data. The main features of the system include product and category management, shopping carts, Midtrans integrated payments, transaction history, reports, as well as a product recommendation system tailored to user preferences. Functional testing conducted with the black box method shows that all functionality functions according to the predetermined plan. Furthermore, the evaluation of usability using the System Usability Scale (SUS) in 30 participants resulted in an average score of 81.75. This value falls into the category of "Acceptable" on the Acceptability Ranges and Grade B ("Good") on the Adjective Rating, which indicates that the system not only meets the standards of good usability, but is also well received by users.

Item Type: Thesis (Skripsi)
Uncontrolled Keywords: Collaborative Filtering, Cosine Similarity, E-Commerce, Laravel, MSME
Subjects: H Social Sciences > HF Commerce > E-Payment
T Technology > Technical Information
T Technology > Technical Information > Software. Aplication
T Technology > Technical Information > Networking > Jaringan Internet
Divisions: Fakultas Komunikasi dan Informatika > S1 Teknik Informatika
Depositing User: RAHMA EVITA AULIASARI
Date Deposited: 19 Feb 2026 05:01
Last Modified: 19 Feb 2026 05:01
URI: http://eprints.ums.ac.id/id/eprint/142770

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