Qushoyyi, Tegar Alam (2025) Penerapan Sistem Rekomendasi Program Kursus Berbasis Website Dengan Klasifikasi K-Nearest Neighbors (K-NN) Pada Brilliant English Course. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
The complexity of choosing an English course program at Brilliant English Course encourages this research to design and build a website-based recommendation system using the K-Nearest Neighbors (KNN) classification algorithm. System development follows the SDLC Waterfall model, including requirements analysis, design, KNN implementation, and testing. The KNN algorithm utilizes a training dataset of historical student profiles and courses that have been selected as target classes (course names) to classify potential new students. The process involves user input data pre-processing (encoding and normalization), Euclidean distance calculation, and recommendation determination based on K nearest neighbors. The result is a web application that provides one to three personalized course recommendations. System evaluation through black-box functional testing and qualitative analysis shows that the system can provide relevant recommendations. The system is expected to facilitate the selection of course programs and support student decision-making more precisely
| Item Type: | Thesis (Undergraduate) | ||||||
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| Uncontrolled Keywords: | Recommendation System, K-Nearest Neighbors, Classification, English Course, Website, Brilliant English Course | ||||||
| Subjects: | 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika | ||||||
| Divisions: | Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika (Sidoarjo) > Tugas Akhir | ||||||
| Depositing User: | Tegar Alam Qushoyyi | ||||||
| Date Deposited: | 04 Aug 2025 01:50 | ||||||
| Last Modified: | 04 Aug 2025 01:50 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/45212 |
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