Perbandingan Naïve Bayes dan Support Vector Machine untuk Klasifikasi Ulasan Pelanggan Indihome - Aan Rohanah; Dwi Latifah Rianti; Betha Nurina Sari (Universitas Indraprasta PGRI Jakarta, 2021)
IndiHome is an internet service provider from PT. Telekomunikasi Indonesia, Tbk with the widest internet coverage in Indonesia. Customer satisfaction is one of the things that must be considered in a company, including the IndiHome company. IndiHome's customer service satisfaction level can be seen from customer reviews via Twitter social media. This study discusses the classification of IndiHome customer reviews by applying the CRISP-DM research stages and the application of the Naïve Bayes Classifier algorithm and the Linear Support Vector Machine Kernel. Customer review data were obtained from Twitter, totaling 1000 tweets using the Rapid Miner and R library tools. The preprocessing stages applied were cleansing, case folding, tokenizing, word conversion, stopword, and stemming. The results of data visualization are presented in the form of a word cloud which is categorized based on positive and negative opinions of words that often appear. The results showed that the application of the Support Vector Machine Kernel Linear algorithm is better than the Naïve Bayes Classifier algorithm with an accuracy value of 82.11%, 76.44% precision, 88.01% recall, and an AUC value of 0.909.