Klasifikasi Review Produk Kecantikan Pada Aplikasi Sociolla Menggunakan Algoritme Modified K-Nearest Neighbor (MK-NN) dengan Pembobotan BM25 - Alfita Nuriza; Indriati Indriati; Nurul Hidayat (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2020)
Beauty products have become one of the many things that cannot be separated from women because of the demands to look beautiful and attractive. These products offer their advantages, there are many beauty products on the market, ranging from skin care and cosmetics from various types and brands. These products have advantages, but not all products suitable for the users needs. This is something that consumers must pay attention to before buying. Other than that, the number of beauty products that are closely related to opinions about certain products in accordance with the parameters given by consumers such as strengths, weaknesses, quality and other parameters, this is what is used as a reference. One electronic trading platform that provides beauty products is Sociolla. Not only sell beauty products, on this platform there are also reviews from consumers. Reading all these reviews in full will take up a lot of time, whereas if you only read a little, the resulting evaluation will be biased. To overcome these problems the classification of the existing review will be classified into 2 classes, namely positive and negative classes. In this study the authors used the Modified K-Nearest Neighbor (MK-NN) algorithm with BM25 as a weighting. The data used were 500 data which were divided into two, positive and negative. From the evaluation results of the test with 5-fold cross validation, the highest average values ​​of accuracy, precision, recall, and f-measure were 51.00%, 50.90%, 52.61%, and 51.70% at the time k = 11.