Analisis Sentimen Pembangunan IKN pada Media Sosial X Menggunakan Algoritma SVM, Logistic Regression dan Naïve Bayes

Abstrak

social media X or formerly more familiar with Twitter is one of the familiar social media and has many users in the world whis is a platform for accesing some information and commenting both suggestions and criticsm related to the development of the Capital City of the Archipelago (IKN) which is the center of smart government in East Kalimantan. There are indormation, suggestions and criticisms addressed to the @ikn_id account directly addressed to the Indonesia government as well as public opinions related to IKN by using the IKN hashtag. Public sentiment on the issue is in the form of text on IKN Development. This research aims to analyze public opinion on the government's decision to build the Capital City of Nusatara (IKN) conveyed through X social media using appropriate data analysis methods by comparing the performance of support vector machine, logistic regression, and naïve bayes algorithms and identifying the most effective algorithm in sentiment analysis. The method used in this research to analyze sentiment are support vector machine, logistic regression and naïve bayes. The use of these three algorithms is also to compare the accuracy that is better than other algorithms. The results obtained using the Support Vector Machine algorithm is 80% while using the Logistic Regression and naïve bayes algorithms are 79%.