Analisis Sentimen Twitter Tentang Isu Resesi 2023: Studi Komparatif Pendekatan Machine Learning
Abstract
Sentiment Analysis adalah metode yang berguna untuk memahami opini publik tentang topik tertentu. Salah satu topik yang menarik perhatian baru-baru ini adalah potensi resesi global pada tahun 2023. Dalam penelitian ini, lima algoritma yang berbeda - Bernoulli Naive Bayes (BNB), Support Vector Machine (SVM), Regresi Linear, K-Nearest Neighbors (KNN), dan Decision Tree - dibandingkan untuk menentukan algoritma mana yang memberikan analisis sentimen yang paling akurat terhadap data Twitter yang terkait dengan topik ini. Hasil penelitian menunjukkan bahwa algoritma SVM memiliki akurasi tertinggi, dan mayoritas pengguna Twitter memiliki sentimen negatif terhadap topik yang berkaitan dengan potensi resesi di tahun 2023, dengan tingkat prediksi sebesar 81,7% dibandingkan dengan 16,3% untuk sentimen positif. Hasil dari penelitian ini diharapkan dapat digunakan untuk memahami sudut pandang masyarakat umum mengenai resesi yang diprediksi akan terjadi pada tahun 2023 dan untuk memberikan wawasan untuk pengembangan kebijakan dan strategi yang bertujuan untuk memitigasi penurunan ekonomi.
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Published
2024-06-30
How to Cite
A’izzah, V., Rianto, R., & Purwayoga, V.
(2024).
Analisis Sentimen Twitter Tentang Isu Resesi 2023: Studi Komparatif Pendekatan Machine Learning.
Jurnal Rekayasa Sistem & Industri (JRSI), 11(01), 14-23.
doi:10.25124/jrsi.v11i01.612
Section
Articles
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
