Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

Sentiment Analysis of Indonesian Responses to the Conflict in Palestine Using KNN and SVM Methods Fauzi, Rizky; Ujianto, Erik Iman Heri
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8725

Abstract

The prolonged conflict between Palestine and Israel has attracted worldwide attention, including Indonesia, which has a history of strong support for the Palestinian cause. This study aims to analyze the sentiment of Indonesian people towards the Palestinian-Israeli conflict using the K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) methods. The subject of this research is user data X (Twitter) which contains opinions about the conflict. After preprocessing, weighting, and labeling, 2960 tweets were collected and classified into three sentiment categories: positive, negative, and neutral. The KNN+SVM method is applied to classify the sentiment of the processed tweet data. The results showed that of the 2960 data analyzed, 33.8% were labeled positive, 38.9% were labeled negative, and 27.4% were labeled neutral with 82% accuracy, 83% precision, 82% recall, and 82% F1-Score. These results show that the majority of Indonesians tend to be negative in expressing their views on the Palestinian-Israeli conflict. This analysis provides greater insight into sentiment patterns in Indonesian responses to sensitive issues, and contributes to the study of public opinion and social dynamics on social media.