Penerapan Algoritma Support Vector Machines dan Random Forest Dalam Analisis Sentimen Ulasan Aplikasi Identitas Kependudukan Digital

The Digital Population Identity (IKD) application, developed by the Directorate General of Population and Civil Registration, aims to streamline access to digital documents and reduce reliance on printed KTPs. Despite its benefits, user reviews from the Play Store highlight significant issues. This research aims to analyze user sentiment towards the IKD application using Support Vector Machines (SVM) and Random Forest algorithms. The study employed these models to classify sentiment in user reviews and used word cloud analysis to further understand the feedback. Results indicate that both the Random Forest and SVM models struggled with accuracy, achieving only 19.25% and 18% respectively. The word cloud analysis revealed a high prevalence of negative reviews, reflecting the app's low rating. These findings suggest that the current sentiment analysis methods are insufficient for capturing the public's opinion on the IKD application, providing crucial insights for improving future digital population identity management strategies.

Keywords: Sentiment, Reviews, Word Cloud, Analysis, Feedback.