Khaerunnizar, L. Muh. and Anton Nugroho, Yohanes (2022) IMPLEMENTASI TEXT MINING TERHADAP ULASAN PENGGUNA DALAM ANALISIS KUALITAS LAYANAN MASKAPAI PENERBANGAN XYZ. ["eprint_fieldopt_thesis_type_tugasakhir" not defined] thesis, University of Technology Yogyakarta.
![[img]](http://eprints.uty.ac.id/style/images/fileicons/text.png) |
Text
5180611151 L. Muh. Khaerunnizar.pdf Download (77kB) |
Abstract
IMPLEMENTASI TEXT MINING TERHADAP ULASAN PENGGUNA DALAM ANALISIS KUALITAS LAYANAN MASKAPAI PENERBANGAN XYZ L. Muh. Khaerunnizar 1, Yohanes Anton Nugroho2 Email: 1khaerunnizar7@gmail.com, 2yohanesanton@uty.ac.id 1,2 Program Studi Teknik Industri, Fakultas Sains & Teknologi, Universitas Teknologi Yogyakarta ABSTRAK Maskapai XYZ merupakan maskapai penerbangan bertaraf rendah (low cost carrier) terbesar di Indonesia dengan pilihan rute penerbangan yang beragam. Berdasarkan pada ulasan yang diberikan oleh pengguna, permasalahan utama yang dihadapi Maskapai XYZ adalah layanan yang buruk. Penelitian ini bertujuan untuk menganalisis kualitas layanan Maskapai XYZ berdasarkan pada sentimen ulasan pengguna, selain itu penelitian ini juga bertujuan untuk mencari faktor-faktor yang menjadi keluhan pengguna dalam ulasannya yang merupakan prioritas perbaikan layanan yang harus dilakukan. Metode text mining dipilih untuk mengolah data ulasan yang berbentuk teks, dengan Naïve Bayes Clasifier untuk mengklasifikasikan sentimen pada ulasan dan algoritma association rule untuk mengetahui hubungan yang terdapat antar kata dalam ulasan. Hasil dari penelitian ini didapatkan sebanyak 34,8% pengguna menganggap layanan yang diberikan oleh maskapai XYZ baik, 32,8% berpendapat netral dan 32,5% menganggap pelayanan yang diberikan buruk. Hasil klasifikasi sentimen diperoleh akurasi sebesar 84,7% dengan kinerja sistem dalam mengklasifikasian kelas positif sebesar 81% dan kelas negatif sebesar 88%. Terdapat 3 faktor yang menjadi keluhan pengguna dalam ulasannya yakni, faktor layanan dengan permasalahan pada delay, durasi check in yang lama sehingga menimbulkan antrian, antrian menuju boarding gate, kompensasi delay yang kurang, bagasi hilang dan rusak serta jatah bagasi kurang. Selanjutnya faktor karyawan dengan permasalahan pada sikap staf yang kurang ramah dan buruk, intonasi suara yang kasar serta sikap abai terhadap penumpang. Terakhir faktor harga dengan permasalahan pada harga bagasi tambahan yang mahal serta harga tiket yang dianggap oleh penumpang tidak sesuai dengan pelayanan yang diberikan. Kata kunci: Analisis sentimen, Text mining, Association rules, Naïve Bayes Clasifier, low cost carrie IMPLEMENTATION OF TEXT MINING TO USER REVIEWS IN AIRLINE XYZ SERVICE QUALITY ANALYSIS ABSTRACT XYZ airline is the largest low-cost carrier in Indonesia with a wide choice of flight routes. Based on the reviews provided by users, the main problem faced by XYZ Airlines is poor service. This study aims to analyze the service quality of XYZ Airlines based on the sentiment of user reviews. Besides that, this study also aims to find factors that become user complaints in their reviews which are the priority of service improvements that must be carried out. The text mining method was chosen to process review data in the form of text, with the Naïve Bayes Classifier to classify sentiment in reviews and an association rule algorithm to determine the relationship between words in the review. This study showed that 34.8% of users considered the service provided by XYZ airline to be good, 32.8% thought it was neutral, and 32.5% considered the service provided terribly. Sentiment classification results obtained an accuracy of 84.7%, with the system's performance in classifying positive classes by 81% and negative classes by 88%. Three factors become user complaints in their reviews, namely, service factors with problems with delays, long check-in durations that cause queues, queues for boarding gates, less compensation for delays, lost and damaged baggage and less baggage allowance. Furthermore, the employee factor with problems in the attitude of the staff who are less friendly and bad, rude voice intonation and neglectful attitude towards passengers. Finally, the price factor with problems with expensive additional baggage prices and ticket prices that passengers consider to be not following the services provided. Keywords: Sentiment analysis, Text mining, Association rules, Naïve Bayes Classifier, low-cost carrier DAFTAR PUSTAKA A. Yani, Dhita Deviacita, Helen Sasty Pratiwi, and Hafiz Muhardi. 2019. “Implementasi Web Scraping Untuk Pengambilan Data Pada Situs Marketplace.” Jurnal Sistem dan Teknologi Informasi (JUSTIN) 7(4): 257. Alwasi’a, Annisa. 2020. “Analisis Sentimen Pada Review Aplikasi Berita Online Menggunakan Metode Maximum Entropy (Studi Kasus: Review Detikcom Pada Google Play 2019) (Undergraduate Thesis).” Universitas Islam Indonesia. Anggara, Afwan, Universitas Teknologi Yogyakarta, Suyud Widiono, and Universitas Teknologi Yogyakarta. 2019. “Klasifikasi Komentar Netizen Terhadap Tokoh Publik Di Instagram Menggunakan Metode Naïve Bayes Classification.” In Prosiding Seminar Nasional Ilmu Komputer (SNIK), Semarang, 1–9. Annur, Haditsah. 2018. “Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes.” ILKOM Jurnal Ilmiah 10(2): 160–65. Azizah, Nur. 2019. “Pengambilan Keputusan Seleksi Penerima Bantuan Rumah Tidak Layak Huni (RTLH) Penduduk Desa Kalianyar Dengan Menggunakan Algoritma Naive Bayes (Undergraduate Thesis).” Universitas Pelita Bangsa. Bae, Wonmi, and Junwook Chi. 2021. "Content Analysis of Passengers' Perceptions of Airport Service Quality: The Case of Honolulu International Airport." Journal of Risk and Financial Management 15(1): 5. Chan, Taizan, Erwin Fielt, Guy Gable, and Karen Stark. 2010. "Business Service Management: Service and Service Quality." Business Service Management project 2(April): 25–27. Chintalapudi, Nalini et al. 2021. "Text Mining with Sentiment Analysis on Seafarers' Medical Documents." International Journal of Information Management Data Insights 1(1): 100005. Dina, Nasa Zata. 2020. "Tourist Sentiment Analysis on TripAdvisor Using Text Mining: A Case Study Using Hotels in Ubud, Bali." African Journal of Hospitality, Tourism and Leisure 9(2): 1–10. Fauzy, Mohamad, Kemas Rahmat Saleh W, and Ibnu Asror. 2016. “Penerapan Metode Association Rule Menggunakan Algoritma Apriori Pada Simulasi Prediksi Hujan Wilayah Kota Bandung.” In Jurnal Ilmiah Teknologi Infomasi Terapan,. Feldman, Ronen, and James Sanger. 2007. 44 Choice Reviews Online The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data. Newyork: CAMBRIDGE UNIVERSITY PRESS. Han, Jiawei, Micheline Kamber, and Jian Pei. 2012. Data Mining Data Mining : Concepts and Techniques : Concepts and Techniques (3rd Edition). second edi. ed. Micheline Kamber. San Francisco: Morgan Kauffman Publisher. http://linkinghub.elsevier.com/retrieve/pii/B9780123814791000010. Inayah, Dwi, and Fredy Law Purba. 2021. “Implementasi Social Network Analysis Dalam Penyebaran Informasi Virus Corona (Covid-19) Di Twitter.” In Seminar Nasional Official Statistics, , 292–99. Institute for Healthcare Improvement. 2016. "Process Analysis Tools: Cause and Effect Diagram." Process Analysis Tools: Cause and Effect diagram: 1–2. Jones, Kasey. 2022. "Model Validation in Python." DataCamp. https://www.datacamp.com/courses/model-validation-in-python (June 20, 2022). Karimi, Zohreh. 2021. "Confusion Matrix." https://www.researchgate.net/publication/355096788_Confusion_Matrix. Katadata.co.id. 2021. “Masyarakat Pilih Mobil Sebagai Moda Transportasi Favorit Liburan Akhir Tahun.” Katadata.co.id. https://databoks.katadata.co.id/datapublish/2021/12/02/masyarakat-pilih-mobil-sebagai-moda-transportasi-favorit-liburan-akhir-tahun (March 15, 2022). Kenyon, George N., and Kabir C. Sen. 2015. The Perception of Quality: Mapping Product and Service Quality to Consumer Perceptions The Perception of Quality: Mapping Product and Service Quality to Consumer Perceptions. Springer. Kurniasari, Siti Rahmi. 2018. “Implementasi SVM Dan Asosiasi Untuk Sentiment Analysis Data Ulasan The Phoenix Hotel Yogyakarta Pada Situs Tripadvisor (Undergraduate Thesis).” Universitas Islam Indonesia. Kusrorong, Neutrino Sae B. Sina, Derwin R.Rumlaklak. 2019. “Kajian Machine Learning Dengan Komparasi Klasifikasi.” Jurnal Komputer & Informatika 7(1). Kwon, Hye Jin, Hyun Jeong Ban, Jae Kyoon Jun, and Hak Seon Kim. 2021. "Topic Modeling and Sentiment Analysis of Online Review for Airlines." Information (Switzerland) 12(2): 1–14. Manning, Christopher D., Prabhakar Raghavan, and Hinrich Schütze. 2009. An Introduction to Information Retrieval. Online Edi. Cambridge: Cambridge University Press. Mardi, Yuli. 2017. “Data Mining : Klasifikasi Menggunakan Algoritma C4.5.” Edik Informatika 2(2): 213–19. Martins, Márcio Ribeiro, Susana Rachão, and Rui Augusto da Costa. 2018. "Electronic Word of Mouth: Does It Really Matter to Backpackers? Booking Website Reviews as an Indicator for Hostels' Quality Services." Journal of Quality Assurance in Hospitality and Tourism 19(4): 415–41. Mulyawan, Rahman. 2016. Birokrasi Pelayanan Publik. ed. Wawan Gunawan. UNPAD Press. Nilam Ramadhani, Abd Wahab Syahroni, Arin Supikar, Wildona Zumam. 2020. “Penerapan Market Basket Analysis Menggunakan Metode Multilevel Association Rules Dan Algoritma ML_T2L1 Pada Data Order PT. Unirama.” Jurnal Nasional Informatika dan Teknologi Jaringan 4(2): 71–84. https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/2405. Nursiyono, Joko Ade, and Chusnul Chotimah. 2021. “Analisis Sentimen Netizen Twitter Terhadap Pemberitaan PPN Sembako Dan Jasa Pendidikan Dengan Pendekatan Social Network Analysis Dan Naive Bayes Classifier.” J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika 14(1): 52–58. Odim, Mba Obasi, Adewale Opeoluwa Ogunde, Bosede Oyenike Oguntunde, and Samuel Ayodele Phillips. 2020. "Exploring the Performance Characteristics of the Naïve Bayes Classifier in the Sentiment Analysis of an Airline's Social Media Data." Advances in Science, Technology and Engineering Systems 5(4): 266–72. Panduwinasari, Elsya, Aang Afandi, and Hesti Wahyuni. 2020. "Low Cost Carrier in Airlines: In Terms of Cost Perspective." In 1st Annual Management, Business and Economic Conference (AMBEC 2019),. Perhubungan Udara Jendral, Direktorat. 2022. “Data Angkutan Udara - Siaga Covid-19.” Kementerian Perhubungan Republik Indonesia. https://sisfoangud.dephub.go.id/siaga-covid19/ (March 20, 2022). Pradana, Musthofa Galih, Azriel Christian Nurcahyo, and Pujo Hari Saputro. 2020. “Pengaruh Sentimen Di Sosial Media Dengan Harga Saham Perusahaan.” Edutic - Scientific Journal of Informatics Education 6(2). Pratama, M. Agung. 2021. 3 “Analisis Perbaikan Kualitas Layanan Pada Aplikasi Zoom Cloud Meetings Berdasarkan Ulasan End-User Menggunakan Metode Text Mining Dan Fishbone Diagram (Undergraduate Thesis).” Universitas Islam Indonesia. https://dspace.uii.ac.id/handle/123456789/31709. Qeis, Muhammad Iqbal. 2015. “Aplikasi Wordcloud Sebagai Alat Bantu Analisis Wacana.” In Conference: International Conference on Language, Culture, and Society - ICLCS LIPI, Jakarta, 1–7. Refaeilzadeh, Payam, Lei Tang, and Huan Liu. 2008. Cross-Validation. Ross, Samantha Michele Mylocopos. 2019. "Backpackers’ Expectations of Hybrid Hotels: A Text Mining Approach.” MODUL University Vienna. Sagin, Ayse Nur, and Berk Ayvaz. 2018. “Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector.” Southeast Europe Journal of Soft Computing 7(1). Shin, Terence. 2021. “Several Model Validation Techniques in Python.” Towards Data Science. https://towardsdatascience.com/several-model-validation-techniques-in-python-1cab3b75e7f1 (June 18, 2022). Statista.com. 2022. “Number of Domestic Air Passengers in Indonesia from 2013 to 2020.” Statista Research Department. https://www.statista.com/statistics/977206/indonesia-domestic-air-passengers/ (March 15, 2022). Sumarsid. Atik Budi Paryanti et al. 2022. “Pengaruh Kualitas Layanan Dan Harga Terhadap Kepuasan Pelanggan Pada Grabfood(Studi Wilayah Kecamatan Setiabudi).” Jurnal Ilmiah M-Progress 12(1): 70–83. Suyanto, Dr. 2019. Data Mining Untuk Klasifikasi Dat. Bandung: INFORMATIKA. Tegar Satria, Aditya, Mustafid, and Dinar Mutiara Kusumo Nugraheni. 2020. “Implementation of Integrated Bayes Formula and Support Vector Machine for Analysing Airline’s Passengers Review.” In E3S Web of Conferences,. Tripadvisor.com. 2022. “Tentang TripAdvisor.” https://tripadvisor.mediaroom.com/id-about-us (March 26, 2022). Utomo, Mardi Siswo. 2015. “Stopword Dinamis Dengan Pendekatan Statistik.” Jurnal Informatika Upgris (JIU) 1(2): 140–48. Wan Fen, Chua, Maizatul Akmar Ismail, Tasnim M A Zayet, and Kasturi Dewi Varathan. 2020. “Sentiment Analysis of Users’ Perception Towards Public Transportation Using Twitter.” International Journal of Technology Management and Information System 2(1): 92–101. http://myjms.moe.gov.my/index.php/ijtmis. Wibowati, JanuarIda. 2021. “Pengaruh Kualitas Pelayanan Terhadap Kepuasan Pelanggan Pada Pt Muarakati Baru Satu Palembang.” Jurnal Manajemen 8(2): 15–31. Wibowo, Antoni. 2017. “10 Fold-Cross Validation.” Master Of Information Technology, BINUS University. https://mti.binus.ac.id/2017/11/24/10-fold-cross-validation/ (May 1, 2022). Zanini, Nadir, and Vikas Dhawan. 2015. “Text Mining: An Introduction to Theory and Some.” Research Matters: A Cambridge Assessment publication 19: 38–44.
| Item Type: | Thesis (["eprint_fieldopt_thesis_type_tugasakhir" not defined]) |
|---|---|
| Subjects: | T Technology > TS Manufactures |
| Divisions: | Fakultas Sains dan Teknologi > S1 Teknik Industri |
| Depositing User: | Kaprodi S1 Teknik Industri UTY |
| Date Deposited: | 09 Dec 2022 03:56 |
| Last Modified: | 09 Dec 2022 03:56 |
| URI: | http://eprints.uty.ac.id/id/eprint/11803 |
Actions (login required)
 |
View Item |
