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Journal : Edu Komputika Journal

Sentiment Analysis of Visitor Reviews on Baturaden Tourist Attraction Using Machine Learning Methods Afrad, Mahazam; Febrianto, Dany Candra; Wijayanto, Sena; Fathoni, M. Yoka
Edu Komputika Journal Vol. 11 No. 1 (2024): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v11i1.10561

Abstract

This study evaluates the performance of four machine learning models: Support Vector Machine (SVM), Random Forest, K-Nearest Neighbors (KNN), and Naive Bayes in analyzing visitor reviews of the Lokawisata Baturaden tourist attraction. Using 5-fold cross-validation, the study aims to determine which machine learning model best suits sentiment analysis on the Baturaden review data. This study was conducted through several stages, including data preprocessing, feature extraction, and the data training process. Case folding, text cleaning, tokenization, stopword removal, and stemming were performed during the data preprocessing stage. The feature extraction method used was TF-IDF. SMOTE was applied to increase data variation and address the data imbalance in the dataset. The results show that SVM provides the best performance with an accuracy of 0.937, an F1-score of 0.937, a precision of 0.943, and a recall of 0.937. Random Forest also performs well with an accuracy of 0.918 and an F1-score of 0.918, though slightly below SVM. KNN shows the lowest performance with an accuracy of 0.651 and an F1-score of 0.544, while Naive Bayes performs adequately with an accuracy of 0.845 and an F1-score of 0.841. Based on this evaluation, SVM is recommended as the best model for sentiment analysis of reviews, followed by Random Forest as a good alternative. The KNN model is not recommended due to its lower performance, while Naive Bayes can be considered for its speed and simplicity, although its results are not as good as SVM and Random Forest. These conclusions guide the selection of the optimal model to enhance understanding and visitor experience at the Baturaden tourist attraction.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Adanti Wido Paramadini Ade Tiara Rosalinda Alfarisi, Gitasari Kurnia Ali, Nizar Alika, Shintia Dwi Anggraeni, Selly Apriliana Puspitaningrum Ardi Susanto Ardi Susanto Arif Riyandi Aruga Yudish Firmansyah Ayu Kusumaningtyas Ayu Nirwana, Zahra Fikri Azzahra, Anisa Cahyo Prihantoro Dairoh Dairoh Dandi Sunardi Dany Candra Febrianto Darmansah Darmansah, Darmansah Dasril Aldo Dea Caesy Rahmadani Dedy Agung Prabowo Dega Surono Wibowo Dega Surono Wibowo, Dega Surono Dwi Januarita Dwi Januarita Dwi Mustika Kusumawardani, Dwi Mustika Fadhilah, Syifa Nur Fajriyah, Nindi Ilmiyati Farkhan Hariyadi Berbudi Bowoleksono Fauzi, Faiq Firmansyah, Aruga Yudish Firmansyah, Muhammad Raafi'u Friliyani, Radiyana Aniq Garin Indra Prameswara Hutanti Setyodewi Ike Kurnia Putri Irwan Susanto Jihan Shinta Celina Kusuma Ningrum, Linda Ayu Lina Fatimah Lishobrina Logiandani Logiandani M Nishom M Nishom Mahazam Afrad Maulida, Elsa Miftahul Jannah Monsya Juansen Muhamad Albirra Arsyi Rizqi Muhamad Awiet Wiedanto Prasetyo Muhammad Fikri Hidayattullah Muhammad Imanullah Nabila Azahra Naufal Ibrahim Nevandra Putra Andyka Ni Wayan Wardani Nicolaus Euclides Wahyu Nugroho Nindi Ilmiyati Fajriyah Nishom, M Nunik Oktaviani Olivia Sari Purba, Yessi Pahrizal, Pahrizal Pero Roberto Kristovic Radiyana Aniq Friliyani Rahmadani, Dea Caesy Raihan Zidane Ramadhan Ramadhan, Firman Adi Ramadhani S, Bunga Rona Nisa Sofia Amriza Safhira Nanda Rahmadhani Salsabila Cahya Alifia Sandhy Fernandes Sandhy Fernandez Sayyidah Jasinda Amalia Selly Anggraeni Sena Wijayanto Setyodewi, RR Hutanti Sisilia Thya Safitri Siti Khomsah, Siti Sudianto Sukmadiningtyas Sulaeman, Gilang Syabrian, Izma Syifa Nur Fadhilah Tegar Wahyudi Adha Tomy Nanda Putra Toni Anwar Toni Anwar Toyib, Rozali Waliulu, Raditya Faisal Wiedanto, Muhammad Awiet Yedija Maarende, Tigris Yogo Dwi Prasetyo Yogo Dwi Prasetyo Yohani Setiya Rafika Nur Yulia Darmi Yustia Hapsari Zahra Fikri Ayu Nirwana