ANALISIS SENTIMEN REVIEW WISATAWAN PADA OBJEK WISATA UBUD MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

I Wayan Budi Suryawan; Nengah Widya Utami; Ketut Queena Fredlina

doi:10.51401/jinteks.v5i1.2242

Authors

I Wayan Budi Suryawan STMIK Primakara
Nengah Widya Utami STMIK Primakara
Ketut Queena Fredlina STMIK Primakara

DOI:

https://doi.org/10.51401/jinteks.v5i1.2242

Keywords:

Ubud, Sentimen Analysis, Support Vector Machine, TripAdvisor, Confusion Matrix.

Abstract

Since the world was hit by the Covid-19 pandemic, it had an impact on activities in Ubud. According to the Central Bureau of Statistics from Bali, the number of foreign tourists visiting from January to October 2021 has decreased by 99.996 percent. On October 14 2021 tourist attractions in Ubud began to reopen. Based on these problems, this research will carry out sentiment analysis from reviews on the TripAdvisor site on tourist attractions in Ubud using the Support Vector Machine algorithm with the Knowledge Discovery in Database method. The results obtained in this study resulted in 551 positive sentiment and 118 negative sentiment based on 669 data test, these results resulted in a positive value for tourist attractions in Ubud. Testing will be carried out on the Support Vector Machine algorithm using the Confusion Matrix which gets good results in conducting sentiment analysis with an accuracy of 84.01%, a recall of 89.83%, a precision of 90.40% and an F1-Score of 90. 11%.

References

Sunarsih, N. M., dkk, 2020. “Strategi Optimalisasi Psikologis Pada Karyawan Yang Dirumahkan Saat Pandemi Covid-19 Di Desa Ubud.” … Di Masa Pandemi Covid … 1–4.

BPS. 2016. “Perkembangan Pariwisata Provinsi Bali 2016.” Bali.Bps.Go.Id (10/02/51/Th.XIV):1–7.

Indra, Rahman. 30 November 2021. “Geliat Ubud Pasca Pariwisata Bali Dibuka Kembali.” CNN Indonesia. (https://www.cnnindonesia.com/gaya-hidup/20211121160803-269-724087/geliat-ubud-pasca-pariwisata-bali-dibuka-kembali).

Eaggeliony, Jenifer Christy. 19 Mei 2022. “Sejumlah Objek Wisata Di Bali Kembali Dipadati Pengunjung - Bali - Bisnis.Com.” Bisnis.Com. (https://bali.bisnis.com/read/20220517/538/1533945/sejumlah-objek-wisata-di-bali-kembali-dipadati-pengunjung?utm_source=Google News&utm_medium=Partnership&utm_campaign=Digital Marketing).

Muhammad Arhami, Muhammad Nasir. 2020. “Data Minig Algoritma Dan Implementasi.” DATA MINING Algoritma Dan Implementasi 2.

Saputra, Yogi Aditya, Syafrial Fachri Pane, and Rolly Maulana Awangga. 2020. BIG DATA: IMPLEMENTASI HADOOP MAPREDUCE PADA PEMETAAN SEKOLAH MENGGUNAKAN PYTHON. Kreatif Industri Nusantara. Bandung.

Nur Akbar, Muhammad, and Nur Annisa Safitri Yusuf. 2022. “Analisis Sentimen Pengguna Indihome Dengan Metode Klasifikasi Support Vector Machine (SVM).” Journal Shift Vol 2(1):13–21.

Widya Utami, Nengah, and Made Artana. 2022. “Text Mining Dalam Analisis Sentimen Pembelajaran Daring Di Masa Pandemi Covid 19 Menggunakan Algoritma K-Nearest Neighbor.” Jurnal Informatika Teknologi Dan Sains 4(2):140–48. doi: 10.51401/jinteks.v4i2.2034.

Liu, Bing. 2015. “Opinions, Sentiment, and Emotion in Text.” 381. Cambridge University Press. New York.

R. H. Fikri Aldi Nugraha, Nisa Hanum Harani, Analisis Sentimen Terhadap Pembatasan Sosial Menggunakan Deep Learning - Google Books. Kreatif Industri Nusantara, 2022. Accessed: Nov. 25, 2021. [Online]. Available: https://books.google.co.id/books?id=f738DwAAQBAJ&printsec=frontcover&hl=id#v=onepage&q&f=false

Fikri Aldi Nugraha, Nisa Hanum Harani, Roni Habibi. 2022. Analisis Sentimen Terhadap Pembatasan Sosial Menggunakan Deep Learning - Google Books. edited by R. M. Awangga. Kreatif Industri Nusantara.

Fadilah, Evi. 2019. “Implementasi Metode Profile Matching Terhadap Sistem Pendukung Keputusan Penerimaan Dana Zakat Pada Badan Amil Zakat Pertamina (BAZMA).” Matics 10(2):39. doi: 10.18860/mat.v10i2.5745.

Dennis, Aprilla. 2013. “Belajar Data Mining Dengan RapidMiner.” Innovation and Knowledge Management in Business Globalization: Theory & Practice, Vols 1 and 2 5(4):1–5.

Djufri, Mohammad. 2020. “Penerapan Teknik Web Scraping Untuk Penggalian Potensi Pajak (Studi Kasus Pada Online Market Place Tokopedia, Shopee Dan Bukalapak).” Jurnal BPPK?: Badan Pendidikan Dan Pelatihan Keuangan 13(2):65–75. doi: 10.48108/jurnalbppk.v13i2.636.

Josi, Ahmad, Leon Andretti Abdillah, and Suryayusra. 2014. “Penerapan Teknik Web Scraping Pada Mesin Pencari Artikel Ilmiah.”

Yunarfi, Geovaldo Reggie, Ricky Simdy, and Jackson. 2021. “Implementasi Text Mining Untuk Mengetahui Kata Abreviasi Dalam Percakapan Media Sosial.” Journal of Digital Ecosystem for Natural Sustainability (JoDENS) 1(2):78–83.

Adiwijaya, Igg, 2006, Text Mining Dan Knowledge Discovery, Kolokium Bersama Komunitas Datamining Indonesia & Soft-Computing Indonesia 1–9.

Zakiyuddin, Hizbu, Apriani. 2021. “Penerapan Algoritma Cosine Similarity Dan Pembobotan TF-IDF Pada System Penerimaan Mahasiswa Baru Universitas Bumigoram Mataram.” 1–7.

Budiman, Irwan, and Retma Ramadina. 2015. “Penerapan Fungsi Data Mining Klasifikasi Untuk Prediksi Masa Studi Mahasiswa Tepat Waktu Pada Sistem Informasi Akademik Perguruan Tinggi.” Ijccs x, No.x(1):1–5.

Oki Oktaviarna Tensao, I Nyoman Yudi Anggara Wijaya, and Ketut Queena Fredlina. 2022. “Analisa Data Mining Dengan Algoritma K-Means Clustering Untuk Menentukan Strategi Promosi Mahasiswa Baru Pada STMIK Primakara.” INFORMASI (Jurnal Informatika Dan Sistem Informasi) 14(1):1–17. doi: 10.37424/informasi.v14i1.135.

Kowalczyk, Alexandre. 2017. “Support Vector Machines Succintctly, Syncfusion.” Succinctly E-Book Series 114.

Saputro, Irkham Widhi, and Bety Wulan Sari. 2020. “Uji Performa Algoritma Naïve Bayes Untuk Prediksi Masa Studi Mahasiswa.” Creative Information Technology Journal 6(1):1. doi: 10.24076/citec.2019v6i1.178.

[23] Karsito, and Santi Susanti. 2019. “Klasifikasi Kelayakan Peserta Pengajuan Kredit Rumah Dengan Algoritma Naïve Bayes Di Perumahan Azzura Residencia.” Jurnal Teknologi Pelita Bangsa 9:43–48.

Ibnu Daqiqil Id. 2021. MACHINE LEARNING?: Teori, Studi Kasus Dan Implementasi Menggunakan Python. Riau: UR PRESS.

Mardi, Yuli. 2017. “Data Mining?: Klasifikasi Menggunakan Algoritma C4.5.” Edik Informatika 2(2):213–19. doi: 10.22202/ei.2016.v2i2.1465.

Diki Hendriyanto, Muhammad, Azhari Ali Ridha, and Ultach Enri. 2022. “Analisis Sentimen Ulasan Aplikasi Mola Pada Google Play Store Menggunakan Algoritma Support Vector Machine Sentiment Analysis of Mola Application Reviews on Google Play Store Using Support Vector Machine Algorithm.” Journal of Information Technology and Computer Science (INTECOMS) 5(1):1–7.

Ramos, Sérgio, João Soares, Samuel S. Cembranel, Inês Tavares, Z. Foroozandeh, Zita Vale, and Rubipiara Fernandes. 2021. “Data Mining Techniques for Electricity Customer Characterization.” Procedia Computer Science 186:475–88. doi: 10.1016/j.procs.2021.04.168.

Muhammadin, Alman, and Irwan Agus Sobari. 2021. “Analisis Sentimen Pada Ulasan Aplikasi Kredivo Dengan Algoritma SVM Dan NBC.” 2(2):85–91.