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All Journal Jurnal Ilmu Komputer CAUCHY: Jurnal Matematika Murni dan Aplikasi Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Aplikasi Statistika & Komputasi Statistik JTIM : Jurnal Teknologi Informasi dan Multimedia Jurnal Bumigora Information Technology (BITe) Jurnal Teknimedia: Teknologi Informasi dan Multimedia IJISTECH Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Jurnal aplikasi IPTEK
Rizal, Ahmad Ashril
Universitas Islam Negeri Mataram
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : CAUCHY: Jurnal Matematika Murni dan Aplikasi

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Sentiment Analysis on Government Performance in Tourism During The COVID-19 Pandemic Period With Lexicon Based Priadana, Adri; Rizal, Ahmad Ashril
CAUCHY Vol 7, No 1 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i1.12488

Abstract

The COVID-19 pandemic impact has affected all industries in Indonesia and even the world, including the tourism industry. Researchers have a role in researching to answer the needs of the tourism industry, especially in making tourism and business destination management programs and carrying out activities oriented to meet the needs of the tourism industry. Meanwhile, the government has a role in making policies, especially in the roadmap, for developing the tourism industry. This study aims to track trending topics in social media Instagram since COVID-19 hit. The results of trending topics will be classified by sentiment analysis using a Lexicon-based and Naive Bayes Classifier. Based on Instagram data taken since January 2020, it shows the five highest topics in the tourism sector, namely health protocols, hotels, homes, streets, and beaches. Of the five topics, sentiment analysis was carried out with the Lexicon-based and Naive Bayes classifier, showing that beaches get an incredibly positive sentiment, namely 80.87%, and hotels provide the highest negative sentiment 57.89%. The accuracy of the Confusion matrix's sentiment results shows that the accuracy, precision, and recall are 82.53%, 86.99%, and 83.43%, respectively.
Co-Authors Abdurahim Abdurahim Adam Bachtiar Maulachela Adri Priadana Akbar Juliansyah Biyas Ola Tafakkur Dara Puspita Anggraeni Dedi Rosadi Dwi Ratnasari Fahrurrozi Gibran Satya Nugraha Hermansah Hermansah Ismarmiaty Jian Budiarto Jian Budiarto Jian Budiarto Khairunnazri Lalu Abd Rahman Hakim Lalu Puji Indra Kharisma Lalu Puji Indra Kharisma Lalu Puji Indra Kharisma Lalu Puji Indra Kharisma Lalu Puji Indra Kharisma M. Saleh Sofyan Maria Nuzurana Asti Mohammad Faisal Kholid Muh. Fahrurrozi Siti Soraya Syahroni Hidayat Thifal Baraas Titi Supianti Yunita Astuti