Analisis dan Perbandingan Sentimen Lirik Lagu pada Album Logic Mess dan Life Update Karya Arash Buana Menggunakan NRC Emotion Lexicon - Kimi Thora Refolino; James Aldo Parlindungan; Woro Isti Rahayu (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh, 2026)
Song lyrics are a form of textual data that can be analyzed using Natural Language Processing (NLP) to identify the emotional patterns contained within them. This study aims to analyze and compare the emotional distribution in the lyrics of Arash Buana’s albums Logic Mess and Life Update using the NRC Emotion Lexicon. The dataset consists of lyrics from 20 songs, including 10 songs from Logic Mess and 10 songs from Life Update. Data were collected through a web scraping technique and processed using several preprocessing stages, including case folding, tokenization, and stopword removal. Emotion analysis was conducted by matching the resulting tokens with emotion categories in the NRC Emotion Lexicon. The results indicate that Logic Mess is dominated by negative emotion (18.49%), followed by sadness (12.22%), anger (10.77%), and fear (10.61%), reflecting a more reflective and melancholic emotional character. In contrast, Life Update is dominated by positive emotion (17.91%), followed by joy (11.23%), sadness (11.23%), and anticipation (11.08%), indicating a more optimistic emotional tendency. Comparative analysis reveals an increase in positive emotions and a decrease in negative emotions in Life Update. These findings demonstrate that the NRC Emotion Lexicon-based NLP approach can systematically and effectively identify and compare emotional characteristics in song lyrics. Despite limitations in interpreting contextual nuances, metaphors, and irony, the NRC Emotion Lexicon enables systematic emotion mapping and contributes to computational musicology and psychological studies of creative works.