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Analysis of Airline Passenger Satisfaction Using Decision Tree and Naïve Bayes Algorithms

Devita Sertivia Suprapto Information Systems Department, Faculty of Engineering and Informatics, Universitas Multimedia Nusantara Raymond Oetama Information Systems Department, Faculty of Engineering and Informatics, Universitas Multimedia Nusantara DOI: https://doi.org/10.37034/infeb.v5i4.728 Keywords: Airline Passenger Satisfaction, Decision Tree, Naïve Bayes, In-Flight Services, Customer Satisfaction Abstract In the dynamic landscape of airline services, comprehending the intricacies that mold customer satisfaction is paramount to elevating overall service quality. This study aspires to dissect these pivotal elements, contributing nuanced insights that can propel the enhancement of customer satisfaction within the industry. A multifaceted investigation encompasses analyzing demographic data, exploring underlying factors significantly shaping passenger satisfaction, and identifying the most adept model for forecasting imminent passenger satisfaction outcomes. A model was meticulously crafted by leveraging a decision tree algorithm to discern the substantial variables influencing passenger satisfaction. Simultaneously, the Naïve Bayes algorithm was harnessed to prognosticate forthcoming passenger satisfaction. The findings underscore the diverse facets of the flying experience impacting satisfaction, with both ctree and rpart decision tree algorithms spotlighting critical factors, such as online boarding, inflight entertainment, WiFi service, class, and travel type. The Naïve Bayes algorithm demonstrates around 87% accuracy in predicting passenger satisfaction, underscoring its efficacy in discerning patterns within this complex realm. Downloads Download data is not yet available. References Ashwika, Dishali G K, & Hemalatha N. (2020). Airline Passenger Satisfaction Prediction Using Machine Learning Algorithms. Redshine Archive, 1, 8–24. DOI: https://doi.org/10.25215/8119070682.24 . Ban, H. J., & Kim, H. S. (2019). 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Implementasi Algoritma Decision Tree dan Naïve Bayes Untuk Klasifikasi Sentimen terhadap Kepuasan Pelanggan Starbucks. Journal of Information System Research (JOSH), 4(2), 641–649. DOI: https://doi.org/10.47065/josh.v4i2.2949 .	Download Published 2023-12-31 Issue Vol. 5, No. 4 (2023) Section Articles How to Cite Suprapto, D. S., & Oetama, R. (2023). Analysis of Airline Passenger Satisfaction Using Decision Tree and Naïve Bayes Algorithms. Jurnal Informatika Ekonomi Bisnis, 5(4), 1493-1500. https://doi.org/10.37034/infeb.v5i4.728 ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX This work is licensed under a Creative Commons Attribution 4.0 International License.

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