Analisis Sentimen Aplikasi Get Contact di APP Store Menggunakan Metode SVM (Support Vector Machine) - Aulia, Narisa; Sari, S N; Wakhidah, N (Politeknik Harapan Bersama, 2025)
Current technological developments have led to a variety of new innovations to create applications that make it easier for users to manage phone calls, one of which is the Get Contact application. By managing phone calls, it is hoped that it will help users to minimize the occurrence of fraud or the like. The goal is to analyze user sentiment towards the Get Contact application by classifying user reviews into positive and negative categories through sentiment analysis. The Support Vector Machine method is used in this analysis process with a linear kernel approach to determine the accuracy of the Get Contact application review classification. The stages used in this research include data collection, preprocessing, labeling, split data, SVM model training, and model evaluation. This study shows that the Support Vector Machine (SVM) method classification of sentiment analysis of Get Contact application reviews on the App Store produces an accuracy value of 95.50%, negative precision 0.96, positive precision 0.95, negative recall 0.95, positive recall 0.96, positive and negative f-1 scores are the same, amounting to 0.95. As for the results of the most reviews are negative reviews with a negative review percentage of 94.8%, while for positive reviews it is 5.2%.