PENERAPAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DALAM ANALISIS SENTIMEN PENGARUH BRAND IMAGE DAN LABEL HARGA: STUDI ANALISIS: PRODUK SKINCARE SKINTIFIC - Lathifah, Ekarini; Wicaksono, Aditya Dwi Putro; Wijaya, Andreas Rony (P3M Politeknik Negeri Banjarmasin, 2024)
There are various kinds of products that are included in cosmetic products, namely personal care, make up, fragrance including perfume, hair care, and skincare. Skincare has become one of the primary needs for women in Indonesia today, because skincare can maintain healthy skin. Skincare is a beauty product that is used by users to clean dirt on the face. In deciding to choose skincare products, of course, consumers are influenced by various factors such as skincare quality, brand image, price, and others. In addition, reviews of skincare products are also important as an effort by cosmetic companies to attract consumers' buying interest. One method in deep learning to analyze is the Convolutional Neural Network (CNN). Sentiment analysis is carried out as an effort to evaluate and determine consumer satisfaction with skincare products as well as materials for service improvement. This study uses the CNN method which in this model has several stages such as data scraping, data preprocessing which consists of data cleansing & case folding, stemming, tokenizing, filtering (stopword removal), labeling process, modeling, and model evaluation. In this study, the data used is scraping data on the Tokopedia website about skincare skintific products. The data will be processed with the CNN model to obtain an accuracy value resulting from the performance of the model.