Implementation of the K-Means Clustering Method for Airline Sentiment Analysis in Indonesia

DOI

10.2991/978-94-6463-668-0_5How to use a DOI?

Keywords

K-Means Clustering; Sentiment Analysis; Classification; Airline Services

Abstract

Flight Services are activities provided by Air Transport Business Entities including before the flight (pre-flight), during the flight (in-flight), and after the flight (post flight). With the increasing number of domestic and international companies operating and providing flight services with various facilities and costs, airlines are working hard to ease this burden. By providing the services that consumers expect, airlines will continue to be in demand by consumers. Through sentiment analysis, it can help to understand consumer feedback by looking at whether they tend to be negative or positive. This research aims to determine passenger responses regarding airline services in Indonesia based on the classification of positive and negative comments using the K-means Clustering method with the hope that this can become an evaluation material for airlines in providing better services. The data source for this research was obtained from a collection of comments from airline consumers in Indonesia via one of the popular social media, namely Twitter. Retrieving Twitter data by filling in keywords in the database name using the Netlytic website. The test results from 142 tweets, obtained 78 positive opinions and 64 negative opinions and the resulting percentage accuracy value was 95.07%. This shows that aviation services in Indonesia tend to be good and consumers feel satisfied.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Dwi Nugraheny
AU  - Haruno Sajati
AU  - Rama Bayu Suciandi
AU  - Nurcahyani Dewi Retnowati
AU  - Buyung Junaidin
AU  - Heri Sunaryo
PY  - 2025
DA  - 2025/03/31
TI  - Implementation of the K-Means Clustering Method for Airline Sentiment Analysis in Indonesia
BT  - Proceedings of the Adisutjipto Aerospace, Science and Engineering International Conference (AASEIC 2024)
PB  - Atlantis Press
SP  - 28
EP  - 37
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-668-0_5
DO  - 10.2991/978-94-6463-668-0_5
ID  - Nugraheny2025
ER  -