Analisis Sentimen Review Shopee Berbahasa Indonesia Menggunakan Improved K-Nearest Neighbor dan Jaro Winkler Distance - Liana Shanty Wato Wele Keaan; Indriati Indriati; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
The recent development in technology has allowed technology to give ease the lives of the general public. One of the conveniences of the development is an online shopping system. Shopee is one of the available online shopping platforms. Shopee's application has provided convenience in terms of buying and selling one's products online thru a smartphone where all of those features can be accessed. In online shopping activities, the price of sold products is equally important to its quality where it is mostly shown thru reviews. Unfortunately, many consumers have difficulty in understanding certain reviews from other consumers rooting from the usage of non-standard language. Therefore, this research focuses on sentiment analysis research of reviews in the form of text which will be divided into two classes, which are positive and negative. The analysis process is started by preprocessing, word weighting thru TF-IDF, followed by normalization, and cosine similarity using the Improved K-Nearest Neighbor and Jaro Winkler Distance to repair words that are not in the standard language. Based on testing of the value of k which is acquired thru evaluation using 5-fold, the optimal value is k=10, after word repairs were done, were a value of 0,876 for accuracy, precision value are 0,810, a recall score of 0,942, and f-measure score of 0,882. Based on the testing results, the accuracy values were fluctuate which were affected by the value of k-values.