Sentiment Analysis untuk Mengidentifikasi Faktor Penunjang Kesuksesan Feeder Wira Wiri Suroboyo - Bellanov, Agrienta; Irawati, Desrina Yusi (Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi, 2025)
Traffic congestion is a major issue in Surabaya, a metropolitan city with a high rate of private vehicle growth. To address this problem, the Surabaya city government launched the Wira Wiri Suroboyo feeder service as a complement to the Suroboyo Bus mass transportation system. This study aims to identify public responses to the service through sentiment analysis of comments posted on the official Instagram account @wirawirisuroboyo. The methodology employed sentiment analysis and text mining techniques using R Studio software. Data were collected via web scraping from 230 comments and processed through data cleaning, tokenization, case folding, and stopword removal. The results show that 37% of comments were positive, 16% expressed trust, 10% were sad, and 8% were negative. A word cloud revealed dominant words such as "halte" (bus stop), "rute" (route), and "bisa" (can), reflecting the community’s need for better accessibility and service coverage. This research contributes as an evaluation input and recommendation for policymakers to improve the quality and distribution of Wira Wiri Suroboyo services, supporting a more inclusive and sustainable public transport system in Surabaya.