Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : building of informatics technology and science

Analisis Sentimen Kenaikan Harga BBM Pertamax Pada Media Sosial Menggunakan Metode Naïve Bayes Classifier Sitio, Sartika Lina Mulani; Nadiyanti, Ria
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2311

Abstract

Fuel Oil (BBM) is a very vital commodity. Fuel has an important role in people's lives. Because of the importance of fuel in people's lives, fuel is one of the basic needs of the community. The policy of increasing the price of fuel has always been a phenomenon in various media which causes pros and cons in society. The policy of increasing fuel prices has a big impact on society, both direct and indirect consumption. This study aims to explore public opinion, whether it shows negative or positive sentiment in the policy of increasing fuel prices. The increase in Pertamax fuel prices has drawn several opinions from citizens on Facebook social media. Sentiment analysis research was conducted to determine the response to Facebook comments on Brilio.Net accounts in 2022 related to the increase in Pertamax fuel prices with a dataset of 799 data, as well as a comparison of the number of positive, negative, and neutral comments. In addition, in this study to be able to determine the level of performance generated by the nave Bayes classifier method in the test. The author uses 80% of the comment dataset to be used as training data and 20% to be used as test data to be used as machine learning and test data. Then the data is classified by the system using orange data mining tools so as to produce a percentage of positive sentiment as much as 19%, negative sentiment as much as 22% and neutral sentiment as much as 59%. testing with the nave Bayes classifier method obtained the highest percentage accuracy rate of 99% from all datasets.
Co-Authors Abed Neco Achmad S.W.A Nurba Ahmad Arifin Ahmad Arifin Arifin Andika Gustiawan Anshar Daud Aries Saifudin Aries Saifudin Ariya Aritonang Bakri, Asri Ady Bayu Fadlan Rosid Bima Guntara Budi Apriyanto Darmawati Darmawati Delfi Yuliana Tanu Deny Setiawan Destin Mahardika Wijayanti Dharma Fathahillah Diki, Muhammad Asshidiqie Efronius Paduansi Entis Sutrisna Ester, Ria Faizi, Billy Nur Fajar Agung Nugroho Farida Nurlaila Fauzan, Wildan Tino Fazriansyah, Reza Fikri Alfiansyah Fiqih Wijaya Firman Aziz Saputra Fitri Miladiyah, Citra Gama, Fernando Hardiansyah hidayatullah Al Islami Ilham Pratama Ilham, Farizi Irpan Kusyadi Irpan Kusyadi Kusyadi Iwan Giri Waluyo Joko Suwarno Judijanto, Loso Julianus Alfario Junianto, Mochamad Bagoes Satria Khaidar, Ahmad Al Lely Panca Andriyanto Mahir, Shafa mohadib mohadib Muhamad Shafly Pratama MUHAMMAD AGIL Muhammad Al Fatih Muhammad Asshidiqie Diki Muhammad Chesta Adabi Putra Muhammad Rivaldi Bachtiar Nadiyanti, Ria Nanang Nanang Nardiono Nardiono Nardiono Nardiono Nardiono, Nardiono Nazar Fadhil Abdullah Nurhasanah Putra, Wahyu Aldi Ramadhan, Syahrul Ghufron Rausan Fikri, Genta Ridwan Rizki Maulana, Rizki Rizky Ramadhani Safitri, Andin Eka Sariadi, Slamet Solihin Solihin Suryaningrat, Suryaningrat Susanna Dwi Yulianti K Suwarno Herry, Ayni Syaeful Machfud Syarif Hidayatullah Testarina Tatiana Hermansyah Teti Desyani Teti Desyani Desyani Widia Novita Sari Willis Puspitasi Sari Yuda Samudra Yulianti Yulianti Yulianti Yulianti Zakaria, Hadi