Analisis sentimen opini masyarakat Indonesia terhadap perdagangan karbon dengan metode VADER

Jourdan, Dustin (2024) Analisis sentimen opini masyarakat Indonesia terhadap perdagangan karbon dengan metode VADER. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Perdagangan karbon menjadi salah satu topik penting dalam upaya mitigasi perubahan iklim di Indonesia. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat Indonesia terhadap perdagangan karbon melalui platform media sosial Quora. Metode yang digunakan dalam penelitian ini adalah analisis sentimen dengan algoritma VADER (Valence Aware Dictionary and sEntiment Reasoner) yang melibatkan dua kamus, yaitu InSet dan SentiStrength_ID. Data dikumpulkan melalui teknik web scraping dari Quora selama periode waktu tertentu. Hasil analisis menunjukkan bahwa sentimen masyarakat Indonesia terhadap perdagangan karbon cenderung positif, dengan distribusi 29 sentimen positif, 11 netral, dan 6 negatif. Kamus InSet menunjukkan kecenderungan lebih banyak sentimen positif, sementara SentiStrength_ID memberikan distribusi sentimen yang lebih seimbang. Perbedaan ini menekankan pentingnya mempertimbangkan berbagai kamus dalam analisis sentimen untuk mendapatkan wawasan yang lebih komprehensif. Penelitian ini diharapkan dapat memberikan gambaran yang berguna bagi pembuat kebijakan dan pemangku kepentingan dalam merancang kebijakan perdagangan karbon yang lebih efektif dan diterima oleh masyarakat. / Carbon trading has become a crucial topic in climate change mitigation efforts in Indonesia. This research aims to analyze the sentiment of the Indonesian public towards carbon trading through the Quora social media platform. The method used in this study is sentiment analysis with the VADER (Valence Aware Dictionary and sEntiment Reasoner) algorithm, involving two dictionaries, namely InSet and SentiStrength_ID. Data were collected through web scraping techniques from Quora over a specific period. The analysis results show that the sentiment of the Indonesian public towards carbon trading tends to be positive, with a distribution of 29 positive sentiments, 11 neutral, and 6 negative. The InSet dictionary shows a tendency for more positive sentiments, while SentiStrength_ID provides a more balanced sentiment distribution. This difference emphasizes the importance of considering various dictionaries in sentiment analysis to gain a more comprehensive insight. This research is expected to provide useful insights for policymakers and stakeholders in designing more effective and publicly accepted carbon trading policies.

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