Citizens needs for smart transportation services in Indonesia: A sentiment analysis approach

Abstract

A smart city (SC) uses technology to enhance the social, economic, and environmental quality of urban life. Consequently, addressing citizens' needs is crucial for successfully implementing smart cities. However, much of the focus has been on technological aspects rather than a comprehensive approach that prioritizes people's needs in a SC. This study investigates the needs of citizens for Smart Transportation Services in Indonesia by analyzing public perceptions using sentiment analysis (SA) based on big data from Twitter. While previous studies have applied SA in marketing and health sectors, its application in public services has not been extensively explored. The Naïve Bayes classifier was used to develop a sentiment classifier due to its higher accuracy compared to other methods. SA of tweets containing the keyword 'transportation' revealed that 47.26% were positive, 42.7% were neutral, and 10.04% were negative, with an accuracy rate of 80%. The research identified four main topics related to citizens' needs for smart transportation services in Indonesia: public transportation, motorbikes, challenges, and traffic congestion. These findings highlight the need to address these issues within the context of SC services in Indonesia.