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All Journal International Journal of Health, Engineering and Technology
Awaliah Fitri Nur Ananda
a:1:{s:5:"en_US";s:27:"Universitas Negeri Makassar";}
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Dentistry Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Comparative Study Of Public Sentiment Analysis On Ikn (Nusantara Capital City) Across X And Youtube Using Pso-Optimized Svm Awaliah Fitri Nur Ananda
International Journal of Health Engineering and Technology Vol. 5 No. 1 (2026): IJHET MAY 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v5i1.752

Abstract

This study aims to compare public sentiment regarding the IKN on Platform X and YouTube using a Polynomial Kernel SVM algorithm optimized by PSO. The method used is an experimental study. Data was obtained through web scraping using Google Colab, yielding 1,413 tweets for the X dataset and 814 for the YouTube dataset. The collected data underwent data cleaning, followed by sentiment labeling of each data point into three classes. Following this, TF-IDF vectorization, PSO-based feature selection, and classification using the Polynomial Kernel SVM were performed. The results of the study showed an accuracy of 76% for the PSO-SVM on the X platform and 75% for the YouTube platform. These results indicate that the PSO-SVM algorithm performs better on the X platform compared to the YouTube platform.
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