Analisis Sentimen Crawling Data dari Sosial Media X tentang Gaza Menggunakan Metode SVM dan Decision Tree

The Palestinian conflict with Israel has attracted a lot of attention from the world, especially in the Gaza Strip after the Hamas group took over the leadership, so that people often make tweets (posts) with various views, some have neutral, positive, negative views. Sentiment analysis is used to analyze data obtained from posts on Twitter. The purpose of this study is to determine the public's views on the Gaza Strip by applying the Decision Tree and Support Vector Machine algorithms to measure their level of accuracy. The results of the sentiment analysis show 805 neutral data, 415 positive, and 308 negative, then the Support Vector Machine algorithm produces the highest level of accuracy with a value of 73.86 which can be categorized as good.

Authors

Institutions

Publication Details

Journal
Jurnal Indonesia Manajemen Informatika dan Komunikasi
Published
2024-12-30
DOI
https://doi.org/10.35870/jimik.v6i1.1225
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analisis Sentimen Crawling Data dari Sosial Media X tentang Gaza Menggunakan Metode SVM dan Decision Tree

Christine Dewi, Nicola Van Robert Jhosefhin
1 citations
Jurnal Indonesia Manajemen Informatika dan Komunikasi
Data Mining and Machine Learning Applications
0.78
article

Analisis Sentimen Crawling Data dari Sosial Media X tentang Gaza Menggunakan Metode SVM dan Decision Tree

Christine Dewi, Nicola Van Robert Jhosefhin
article en
1 citations

Abstract

The Palestinian conflict with Israel has attracted a lot of attention from the world, especially in the Gaza Strip after the Hamas group took over the leadership, so that people often make tweets (posts) with various views, some have neutral, positive, negative views. Sentiment analysis is used to analyze data obtained from posts on Twitter. The purpose of this study is to determine the public's views on the Gaza Strip by applying the Decision Tree and Support Vector Machine algorithms to measure their level of accuracy. The results of the sentiment analysis show 805 neutral data, 415 positive, and 308 negative, then the Support Vector Machine algorithm produces the highest level of accuracy with a value of 73.86 which can be categorized as good.

Jurnal Indonesia Manajemen Informatika dan KomunikasiVol. 6(1)
Satya Wacana Christian University (ID)
Openalex Percentile: Top 18%
Data Mining and Machine Learning Applications
0.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analisis Sentimen Crawling Data dari Sosial Media X tentang Gaza Menggunakan Metode SVM dan Decision Tree — Christine Dewi, Nicola Van Robert Jhosefhin · Jurnal Indonesia Manajemen Informatika dan Komunikasi (2024) | TGRS Research Map | TGRS