Identification of Airport Service Quality using Sentiment Analysis at Soekarno-Hatta International Airport

PT Angkasa Pura II is a state-owned corporation that operates airport services in Indonesia. The increasing number of passengers at Soekarno-Hatta International Airport presents challenges in managing significant traffic growth, which impacts infrastructure and services. Successfully addressing these challenges relies on technological innovation and strategies to enhance service quality with improving passenger satisfaction is crucial as traffic continues to rise. This study aims to assist PT Angkasa Pura II by identifying the most essential features of passengers’ experience based on Airport Service Quality (ASQ) from Airport Council International (ACI) components using Google Maps reviews. This paper also compares the ASQ indicated in the social media reviews to the structure-based questionnaire responses from passengers at the airport in 2023. Based on the sentiment analysis of 17,481 reviews, the study discovers that airport facilities and environment are the most frequently mentioned ASQ aspects of Soekarno-Hatta International Airport. This result demonstrates that PT Angkasa Pura II should mainly focus on these two factors to enhance passengers’ experience and activities at the airport. This research also finds that structure-based surveys might not provide the same data as ASQ produced from sentiment analysis on social media channels. In addition to several factors that contribute to this fact, the usage of social media data has shown to be a way to diversify survey methodologies to gather more complete customer insights

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Publication Details

Journal
Indonesian Journal of Computer Science
Published
2025-02-07
DOI
https://doi.org/10.33022/ijcs.v14i1.4589
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification of Airport Service Quality using Sentiment Analysis at Soekarno-Hatta International Airport

Yova Ruldeviyani, Muhammad Hafiz, Muhammad Afif Gunung, Muhammad Khairunnaziri
Indonesian Journal of Computer Science
Air Traffic Management and Optimization
article

Identification of Airport Service Quality using Sentiment Analysis at Soekarno-Hatta International Airport

Yova Ruldeviyani, Muhammad Hafiz, Muhammad Afif Gunung, Muhammad Khairunnaziri
article en

Abstract

PT Angkasa Pura II is a state-owned corporation that operates airport services in Indonesia. The increasing number of passengers at Soekarno-Hatta International Airport presents challenges in managing significant traffic growth, which impacts infrastructure and services. Successfully addressing these challenges relies on technological innovation and strategies to enhance service quality with improving passenger satisfaction is crucial as traffic continues to rise. This study aims to assist PT Angkasa Pura II by identifying the most essential features of passengers’ experience based on Airport Service Quality (ASQ) from Airport Council International (ACI) components using Google Maps reviews. This paper also compares the ASQ indicated in the social media reviews to the structure-based questionnaire responses from passengers at the airport in 2023. Based on the sentiment analysis of 17,481 reviews, the study discovers that airport facilities and environment are the most frequently mentioned ASQ aspects of Soekarno-Hatta International Airport. This result demonstrates that PT Angkasa Pura II should mainly focus on these two factors to enhance passengers’ experience and activities at the airport. This research also finds that structure-based surveys might not provide the same data as ASQ produced from sentiment analysis on social media channels. In addition to several factors that contribute to this fact, the usage of social media data has shown to be a way to diversify survey methodologies to gather more complete customer insights

Indonesian Journal of Computer ScienceVol. 14(1)
University of Indonesia (ID)
Universitas Indonesia
Openalex Percentile: Top 95%
Air Traffic Management and Optimization
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