IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR PADA WEBSITE REKOMENDASI LAPTOP
DOI:
https://doi.org/10.24002/jbi.v10i1.1847Abstract
Abstract.
There are various types of laptops that make consumers experiencing confusion in determining choices fitting the criteria that consumers want. The K-Nearest Neighbor (K-NN) algorithm was chosen since K-NN algorithm is a model that can classify data based on the closest distance. This system was created to help consumers in choosing a laptop based on purchasing objectives such as for gaming, design, and office, price, also specifications of the desired laptop. This system helps providing a reference to consumers in determining the laptop that suits their needs. Based on consumer satisfaction test which is carried out to ten consumers, eight out of ten people agree to the given recommendations. The percentage of satisfaction is 80%, therefore the created laptop recommendation was considered successful. Keywords: KNN, Recommendation, Selection, Laptop
Abstrak.
Berbagai jenis laptop yang ada membuat konsumen mengalami kebingungan dalam menentukan pilihan yang sesuai dengan kriteria yang konsumen inginkan. Algoritma K-Nearest Neighbor (K-NN) ini dipilih karena algoritma K-NN merupakan suatu model yang dapat mengklasifikasikan data berdasarkan jarak terdekat. Sistem ini dibuat untuk membantu konsumen dalam memilih laptop berdasarkan tujuan pembelian seperti untuk gaming, desain, atau kantor, harga, juga spesifikasi mengenai laptop yang diinginkan. Sistem ini membantu memberikan referensi kepada pengguna atau konsumen dalam menentukan laptop yang sesuai dengan kebutuhan. Berdasarkan uji kepuasan pengguna yang dilakukan kepada sepuluh orang pengguna, delapan dari sepuluh orang menjawab dengan jawaban setuju dengan hasil rekomendasi yang diberikan. Persentase kepuasan terhadap hasil rekomendasi sebesar 80% oleh karena itu rekomendasi laptop yang dibuat dinyatakan berhasil.
Kata kunci: KNN, Rekomendasi, Pemilihan, Laptop
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