Keluwih: Jurnal Sains dan Teknologi https://journal.ubaya.ac.id/index.php/saintek <p align="justify"><strong>Keluwih: Jurnal Sain</strong><strong>s</strong><strong> dan Teknologi&nbsp;</strong>is an online, open access, and peer-reviewed journal. JST publishes two issues per year: in February (covering February-July) and in August (covering August-January). This journal is to provide a forum for the sharing, dissemination, and discussion of original research, case studies, and critical reviews in the fields of science and technology including biotechnology. This focus and scopes include, but are not limited to subjects in industrial engineering, informatics, electrical engineering, manufacture, environmental issues, renewable energi, chemistry and chemical engineering, product design &amp; management, and fashion design &amp; lifestyle products.</p> <p align="justify"><strong>eISSN:&nbsp;</strong>2721-2432</p> en-US <ul> <li class="show" style="text-align: justify;">Articles published in Keluwih: Jurnal Sains dan Teknologi are licensed under a <a title="CC BY SA" href="https://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International</a> license. You are free to copy, transform, or redistribute articles for any lawful purpose in any medium, provided you give appropriate credit to the original author(s) and the journal, link to the license, indicate if changes were made, and redistribute any derivative work under the same license.</li> <li class="show" style="text-align: justify;">Copyright on articles is retained by the respective author(s), without restrictions. A non-exclusive license is granted to&nbsp;Keluwih: Jurnal Sains dan Teknologi to publish the article and identify itself as its original publisher, along with the commercial right to include the article in a hardcopy issue for sale to libraries and individuals.</li> <li class="show" style="text-align: justify;">By publishing in Keluwih: Jurnal Sains dan Teknologi, authors grant any third party the right to use their article to the extent provided by the <a title="CC BY SA" href="https://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International</a> license.</li> </ul> singgih_s@staff.ubaya.ac.id (Singgih Sugiarto) rahmanfibri@staff.ubaya.ac.id (Miftahur Rahman Fibri) Sat, 31 Aug 2024 00:00:00 +0000 OJS 3.1.2.4 http://blogs.law.harvard.edu/tech/rss 60 Sentiment Analysis for Sumber Gempong Rice Field-Based Tourism Destination using Long Short-Term Memory https://journal.ubaya.ac.id/index.php/saintek/article/view/6498 <p style="text-align: justify;"><strong><em>Abstract</em></strong>—<em>Sumber Gempong is a rice field-based tourist destination located in Ketapanrame Village, Trawas District, Mojokerto Regency, East Java Province. It is managed by a village-owned company (BUMDesa Mutiara Welirang). BUMDesa evaluates tourist satisfaction manually by reviewing online comments and it consumes time and labor works. Data used in this research automatically collected from Google Maps Review. Long Short-Term Memory (LSTM) method analyze data of two sentiment labels, positive or negative, based on four categories: facilities, services, culinary, and attractions. The collected dataset has 674 comments consist of 420 positive sentiments and 254 negative sentiments with 320 facilities, 61 services, 125 culinary, and 192 attractions comments. Five LSTM models were trained on each of four categories and an overall category. The trained models of overall, facilities, services, culinary, and attractions categories achieved, respectively, 91.2%, 86.8%, 94.1%, 89.7%, and 95.6% of accuracies. The average result accuracy&nbsp; is 91.48%. The manager of BUMDesa Mutiara Welirang satisfied with the results of the system and the sentiment results can be used as evaluation material for Sumber Gempong.</em></p> <p style="text-align: justify;"><strong><em>Keyword</em><em>s:</em></strong> <em>sentiment anaylsis, LSTM, deep learning, social media, tourism</em></p> <p style="text-align: justify;"><em>&nbsp;</em></p> <p style="text-align: justify;"><strong>Abstrak</strong>—Wisata Sawah Sumber Gempong berada di Desa Ketapanrame, Kecamatan Trawas, Kabupaten Mojokerto dan merupakan tempat wisata alam yang dikelola oleh BUMDesa Mutiara Welirang. Evaluasi terhadap tempat wisata ini dilakukan dengan membaca secara manual ulasan-ulasan yang ditulis di media sosial dan pengamatan pribadi. Banyaknya jumlah ulasan yang ada menjadi kendala dalam melakukan evaluasi karena membutuhkan waktu yang cukup lama. Penelitian ini mengambil data ulasan secara otomatis dari media sosial yang diberi label positif atau negatif berdasarkan empat kategori, yaitu fasilitas, pelayanan, kuliner, dan wahana. Metode <em>Long Short-Term Memory</em> (LSTM) dipakai sebagai alat untuk melakukan analisis sentimen. Pengambilan data secara otomatis mendapatkan 674 ulasan yang dibagi menjadi 420 ulasan positif dan 254 ulasan negatif, &nbsp;dengan 320 ulasan fasilitas, 61 ulasan pelayanan, 125 ulasan kuliner , dan 192 ulasan wahana. Lima buah model dilatih berdasar tiap kategorinya dan kategori secara keseluruhan. Model yang telah dilatih mendapatkan nilai akurasi sebesar 91,2%, 86,8%, 94,1%, 89,7%, dan 95,6% berturut-turut untuk keseluruhan kategori, kategori fasilitas, layanan, kuliner, dan wahana. Rata-rata akurasi mencapai 91,48%. Hasil dari sistem telah diujicobakan kepada manajer BUMDesa Mutiara Welirang dan bisa dipakai sebagai bahan evalusi untuk peningkatan kualitas di Sumber Gempong.</p> <p style="text-align: justify;"><strong>Kata kunci:</strong><em> analisis sentimen, LSTM, deep learning, media sosial, wisata</em></p> Njoto Benarkah, Vincentius Riandaru Prasetyo, Jehuda Rivaldo Soetiyono Copyright (c) 2024 Njoto Benarkah, Vincentius Riandaru Prasetyo, Jehuda Rivaldo Soetiyono https://creativecommons.org/licenses/by-sa/4.0 https://journal.ubaya.ac.id/index.php/saintek/article/view/6498 Thu, 31 Oct 2024 00:00:00 +0000