Implementasi Plugin untuk Content-Based dan Context-Based Recommender System pada Platform Online Learning Skillverse.id Berbasis WooCommerce

Ghufron, Mochamad Rafli (2025) Implementasi Plugin untuk Content-Based dan Context-Based Recommender System pada Platform Online Learning Skillverse.id Berbasis WooCommerce. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Integrasi teknologi dalam pendidikan telah berkembang secara signifikan dalam beberapa dekade terakhir, memungkinkan pembelajaran melampaui buku tradisional melalui internet. Namun, sifat informasi online yang tidak terstruktur memerlukan modul pembelajaran yang terorganisir, yang menyebabkan adopsi sistem e-learning secara luas. E-learning kemudian banyak yang digabungkan dengan e-commerce untuk dijual, biasanya disebut sebagai platform online learning, telah menjadi salah satu inovasi terbaru yang menyediakan akses mudah ke sumber belajar yang terstruktur dan terorganisir. Penelitian ini mengeksplorasi kombinasi e-learning dengan e-commerce berbasis Woocommerce untuk menciptakan platform online learning yang dapat diakses, dengan menerapkan sistem rekomendasi untuk personalisasi pengalaman pengguna. Fokusnya adalah pada penerapan metode Content-Based dan Context-Based Filtering menggunakan plugin WooCommerce Product Recommendation dalam CMS WordPress. Pendekatan ini bertujuan untuk meningkatkan rekomendasi produk berdasarkan relevansi atribut menggunakan tags, meningkatkan penjualan melalui personalisasi pengguna, dan membantu pengguna menemukan kursus yang relevan berdasarkan konteks atau waktu tertentu. Platform yang dikembangkan diuji menggunakan metode black box testing dengan pendekatan equivalence partitioning dengan memastikan setiap fungsi berjalan sesuai dengan spesifikasi yang ditentukan dengan membagi input ke dalam beberapa kelas yang dianggap mewakili semua kemungkinan alur uji. Hasil pengujian menunjukkan 100% untuk fungsi e-commerce, 100% untuk fungsi Content-Based Recommender System, dan 87,5% untuk fungsi Context-Based Recommender System yang membuktikan bahwa platform Skillverse telah berfungsi secara optimal sebagai platform online learning berbasis Woocommerce.
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The integration of technology in education has grown significantly in recent decades, allowing learning to go beyond traditional books via the internet. However, the unstructured nature of online information requires organized learning modules, which led to the widespread adoption of e-learning systems. E-learning is then widely combined with e-commerce for sale, usually referred to as online learning platforms, has become one of the latest innovations that provide easy access to structured and organized learning resources. This research explores the combination of e-learning with Woocommerce-based e-commerce to create an accessible online learning platform, by implementing a recommendation system to personalize the user experience. The focus is on applying Content-Based and Context-Based Filtering methods using the WooCommerce Product Recommendation plugin within the WordPress CMS. This approach aims to improve product recommendations based on attribute relevance using tags, increase sales through user personalization, and help users find relevant courses based on context or time. The developed platform is tested using the black box testing method with the equivalence partitioning approach by ensuring each function runs according to the specified specifications by dividing the input into several classes that are considered to represent all possible test flows. The test results show 100% for the e-commerce function, 100% for the Content-Based Recommender System function, and 87.5% for the Context-Based Recommender System function which proves that the Skillverse platform has functioned optimally as a Woocommerce based online learning platform.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	pendidikan, e-learning, content-based filtering, context-based filtering, CMS WordPress, WooCommerce, WordPress, WooCommerce Product Recommendation, black box testing, equivalence partitioning, education, e-commerce, online learning
Subjects:	T Technology > T Technology (General) > T57.5 Data Processing
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Mochamad Rafli Ghufron
Date Deposited:	22 Jan 2025 08:14
Last Modified:	22 Jan 2025 08:14
URI:	http://repository.its.ac.id/id/eprint/116611

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