Comparison of Support Vector Machine (SVM) and Naïve Bayes Algorithm Performance in Analyzing Garuda Bird Design Sentiment in IKN

Moh Hafiz Raja Pratama , Munthe
Andre Hasudungan , lubis

JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Vol. 8 No. 3Spc (2025): Special Issues 2025: Innovations in Predictive Analytics and Sentiment Analy

The Government's policy in moving the Indonesian Capital City (IKN) is considered controversial, this has given rise to various responses from the public, especially on social media X. This research aims to analyze tweet sentiment related to IKN and compare the two algorithms. In this experiment, we succeeded in collecting 5128 tweet data regarding IKN in the X application, the total amount of IKN data was classified into positive sentiment as 2598 1659 negative data and sentiments. Research objectives, methods used, main results, and implications. This research aims to measure public sentiment towards the design of the Garuda bird as the main symbol of the Indonesian Capital City (IKN) by using a comparison of the performance of the Support Vector Machine (SVM) and Naïve Bayes algorithms in analyzing the sentiment of the Garuda bird design in the IKN. main results, for example: the proportion of positive, negative and neutral sentiment, as well as the factors that most influence sentiment. Implications of research results for government, designers and society.