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All Journal Teknika Journal of Economics, Business, & Accountancy Ventura SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Informatika dan Teknik Elektro Terapan JTT (Jurnal Teknologi Terpadu) Jurnal CoreIT Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Inotera Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi Krea-TIF: Jurnal Teknik Informatika Jurnal Riset Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika Ideguru: Jurnal Karya Ilmiah Guru Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) SINTA Journal (Science, Technology, and Agricultural) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer J-Intech (Journal of Information and Technology) Jurnal Indonesia Raya Sisfo: Jurnal Ilmiah Sistem Informasi Knowbase : International Journal of Knowledge in Database Jurnal Dehasen Mengabdi SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Muhammad Fikry
Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Journal : jurnal computer science and information technology coscitech

 1 
Analisis sentimen larangan penggunaan obat sirup menggunakan algoritma naive bayes classifier Fitri Wulandari; Elin Haerani; Muhammad Fikry; Elvia Budianita
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4781

Abstract

The Indonesian government made a policy to stop consuming syrup as a form of prevention against acute kidney failure, which affects many people in Indonesia. However, the policy has caused a lot of comments from the public. These public comments can be found on YouTube, because YouTube has a large data source opportunity to be used as a research material. These comments can be processed directly without using a machine, but it is less effective and efficient. Thus, the comments are processed using machine learning methods. Based on the earlier research, the naive bayes classifier algorithm tends to be simple and easy to use. In addition, this algorithm also has a high accuracy. The amount of data used in this study is 1000 YouTube comment data related to videos regarding the policy of prohibiting the use of syrup medicine, the comments are divided into 2 category, which are positive class and negative class. The results of labeling 1000 comments obtained 704 negative comments and 296 positive comments. Based on the experiments conducted using python programming language, the highest accuracy was obtained at 74% in 70:30 data split. Furthermore, in the balanced dataset (296 positive and 296 negative comments), the highest accuracy was obtained at 64.70% with in 80:20 data split. These results represent that the naive bayes classifier algorithm is good enough at sentiment analysis about the policy of prohibiting the use of syrup drugs.
Analisa sentimen terhadap kenaikan bbm di twitter (x) menggunakan naive bayes classifier Muhammad Abdillah; Fikry, Muhammad; Yusra; Nazir, Alwis; Insani, Fitri
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6954

Abstract

In early September 2022, there was a shock from the news of the rise in fuel prices. The government decided to increase the price of fuel due to the surge in world oil prices. PT Pertamina (Persero) officially raised the price of Fuel Oil (BBM) one-third of September 2022, at 2:30 PM WIB (Western Indonesia Time). Since the decision, it has sparked opinions from the public. Many people expressed their responses through the social media platform Twitter, both in positive and negative ways. This resulted in both positive and negative sentiments from the public. The data used consisted of 3,000 tweets with the keyword "FUEL PRICE INCREASE," collected from November 1, 2022, to December 1, 2022. This research utilized the Naive Bayes Classifier method, conducted with three comparisons using thresholds ranging from 0.001 to 0.007. The experiment was conducted with three types of data testing: opinion data, mixed data (opinion-non-opinion), and balanced data. Here are the test results: for opinion data, the highest accuracy obtained was 80% with a ratio of 90:10, for mixed data, the accuracy obtained was 67.7% with a ratio of 70:30, and for balanced data, the accuracy obtained was 63.6% with a ratio of 90:10.
Co-Authors -, Yusra Abdillah, Rahmad Ahadi, Ridho Alwis Nazir Ananda, Nuari Andini, Nanda Anggraeni . Anggraeni, Ni Ketut Pertiwi Anna Marina Arnawan Hasibuan Asrianda Asrianda Ayu Fransiska Baehaqi Bahari, Bayu Dwi Prasetya Damayanti, Elok Dermawan, Jozu Detha Yurisna Dinata, Ferdian Arya Diqti, Fadillah Fauziah Eka Pandu Cynthia Eka Pandu Cynthia, Eka Pandu Eko Sumartono, Eko Elin Haerani Elin Haerani Elin Haerani Elvia Budianita Elvina Afriani Fadhilah Syafria Fakhrezi, Muhammad Dzaki Faresya, Natasya Febi Yanto Fitri Insani Fitri Insani Harahap, Nazaruddin Safaat Hasugian, Leonardo Hidayat, Rizki Husaini Ibnu Surya Iis Afrianty Inggih Permana Khaidar, Al Kharrisa Andini, Restu kurnia, fitra Lestari Handayani Lola Oktavia Lola Oktavia Mei Lestari, Mei Muhammad Abdillah Muhammad Affandes Muhammad Dhuha, Teuku Nabil Muhammad Irsyad Muhammad Ravil Muhammad Yani, Muhammad Munadila, Aura Munirul Ula Naharuddin Naharuddin Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Ndruru, Arlan Joliansa Nurcholis Sunuyeko, Nurcholis Nurdin Nurdin Nurdin Nurhapiza, Nurhapiza Oktavia, Lola Pizaini Pizaini Prananda, Alga Putra, Wahyu Eka Putri Mardatillah Rahma Yunita, Rahma Rahmat Rizki Hidayat Rahmatillah, Siska Yuna Ramadanu Putra Reski Mai Candra Rinaldi Syarfianto Ritonga, Sinta Wahyuni Sagala, Ruflica Saputra, Ikhsan Dwi Sayed Omas Tutus Arifta Sayed Sentot Imam Wahjono Sofiah Surya Agustian Suwanto Sanjaya Taufik Hidayat Tiara Dwi Arista Wan Sobri Amin Wirdiani, Putri Syakira Yani, Muhamamd Yani, Susmi Syahfrida Yaskur Bearly Fernandes Yenggi Putra Dinata Yolanda, Khovifah Yossie Yumiati Yuda Zafitra Fadhlan Yusra Yusra Yusra . YUSRA YUSRA Yusra, Yusra Zukhruf, Muhammad Firmansyah