Exploring Sentimen Analysis Using Machine Learning: A Case Study on Partai Demokrasi Indonesia Perjuangan (PDIP) in the 2024 General Election

Kurniawan, Fandi
Al Qorni, Qois

International Journal of Social Science, Education, Communication and Economics
Vol. 2 No. 4 (2023): October

General elections have an important role in democratic systems in all countries. In this context, sentiment analysis plays an important role in revealing the public's views on political parties. This study analyzes sentiment towards the Partai Demokrasi Indonesia Perjuangan (PDIP) in the 2024 General Election using the Naive Bayes algorithm. This method classifies social media content related to PDIP into positive (support) or negative (criticism) categories. The analysis results show 100% precision in identifying positive sentiment, but recall is only 97.11%, indicating that some positive sentiment was missed. For negative sentiment, the precision was 94.33% with a recall of 100%, indicating the ability to recognize negative sentiment but little negative prediction error. This study provides an in-depth understanding of the PDIP's perception in the 2024 General Election, supports better political decision making and provides insight to the PDIP in understanding the public's views.