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All Journal Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi
Husaini, Rahayun
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Computer Science & IT

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Klasifikasi Ulasan Pengguna Tiket Pesawat Online dengan Penanganan Ketidakseimbangan Data Menggunakan SMOTE dengan Machine Learning Husaini, Rahayun; Amrullah Husaini, Rahayun; Pratama, Gede Yogi; Satrani, Azral
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol. 11 No. 3 (2025): Desember 2025
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v11i3.18906

Abstract

The COVID-19 pandemic affected public habits in air travel and increased the use of online ticket booking platforms. This study aimed to analyze sentiment in online flight ticket purchase reviews using the Support Vector Machine and K-Nearest Neighbor methods. The research was conducted by collecting user review data from the Tiket.com website, followed by preprocessing, term weighting using TF-IDF, and classification using both methods. The results show that the Support Vector Machine method achieves an accuracy of 51 percent, while the K-Nearest Neighbor method reaches 55 percent after applying data balancing techniques. This study concludes that both methods are effective in classifying user sentiment and can assist service providers in improving service quality and understanding customer needs
Co-Authors Amrullah Husaini, Rahayun Pratama, Gede Yogi Satrani, Azral