Article Per Year (5 Year)
p-Index From 2020 - 2025
8.258
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Journal of Economics, Business, & Accountancy Ventura Journal of Information Systems Engineering and Business Intelligence Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Tekno Kompak Building of Informatics, Technology and Science Kumawula: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Sisfotek Global Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat IJPD (International Journal Of Public Devotion) Jurnal Teknologi dan Sistem Tertanam Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Data Mining dan Sistem Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Sisfotek Global COMMENT: Journal of Community Empowerment Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Pengabdian kepada Masyarakat (Nadimas) Jurnal Media Borneo Jurnal Informatika: Jurnal Pengembangan IT Jurnal Media Celebes Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science The Indonesian Journal of Computer Science
Alita, Debby
Universitas Teknokrat Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

Published : 51 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Artificial Intelligence and Technology Information

 1 
Sentimen Analisis Vaksin Covid-19 Menggunakan Naive Bayes Dan Support Vector Machine Debby Alita; RB Ali Shodiqin
Journal of Artificial Intelligence and Technology Information Vol. 1 No. 1 (2023): Volume 1 Number 1 March 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v1i1.20

Abstract

Vaccine administration in Indonesia has now reached the booster vaccine stage, various types of vaccines have been given to the Indonesian people from the Sinovac, AstraZeneca, Sinopharm, Moderna, Pfizer vaccines, etc. Not a few Indonesian people use several types of vaccines that are offered up to booster vaccines, but there are some people who think they are still infected with this Covid virus with severe symptoms. Another opinion is that there is also a vaccine. In 2019, people were shocked by a new virus from Wuhan, China, namely the corona virus or called COVID-19 (Corona Virus Disease 2019). The government invites the public to get the Covid-19 vaccine in order to form herd immunity or group immunity to the Covid-19 virus. Sentiment analysis can be used to evaluate a service performance and so on. So the author will conduct a comparison between the Naive Bayer Classifier method and the Support Vector Machine to find out which method is more efficient in knowing people's accurate views of the Covid-19 vaccine. The performance test results of the two methods show that the performance of the Naive Bayes Classifier method (Accuracy 72.88%, Precision 43.49%, Recall 54.95%, and average performance 57.10%) is higher than the average performance of the Support Vector Machine method (Accuracy 77.00% , Precision 75.00%, Recall 7.70%, and average performance 53.52%). Based on the average performance value of the Naive Bayes Classifier method, it can be considered more efficient than the Support Vector Machine method.
Co-Authors ., Rusliyawati Adam Indra Sakti Ade Dwi Putra Ade Setiawan Andi Kurniawan Andi Nurkholis Aris Munandar As Shidiq, M Febrian Asmawati Asmawati Asmawati Asmawati Bambang Satrio Gandhi Chairunnisa fadia alifa Cholid Fadilah Hasri Danuarta, Ervin Dedi Darwis Dinda Titian Lestari Dyah Aminatun Dyah Ayu Megawaty Dyah Ayu Megawaty Emi Suwarni Erliyan Redy Susanto Fadila Shely Amalia Feby Amanda Fenty ariany Handika, H Hasrina, Cut Delsi Hayatunnufus Hayatunnufus Heni Sulistiani Ika Septiana Imam Ahmad Imam Ahmad Indah Sari Irwan Tubagus Isnain, Auliya Rahman jenny anggraini Jepi Supriyanto Krisna, Anan Lathifah L Lathifah Lathifah Lisa Ariyanti Mandasari, Berlinda Miswanto Miswanto Muhammad Najib Dwi Satria Muhammad Pajar Kharisma Putra Muhammad Saefudin Muhtad Fadly Munti Sarida Nur Rokhman Nurhasan Nugroho Nurman Satya Marga Nurman Satya Marga Nuroji Nuroji Permata Permata Prita Dellia Puspaningtyas, Nicky Dwi Pustika, Reza Putra, Ade Dwi Putri Sukma Dewi Rahmawati, Ira Tri Rani, Ni Made Suka RB Ali Shodiqin Rillya Arundaa Riska Amalia Praptiwi S. Samsugi Salsabilla, Tasya SANTIKA, YULI Saputri, Gita Aprinda Sari, Raras Kartika Sena, Fikih Yuhada Setiawansyah Setiawansyah Sigit Priyanta Styawati Styawati suaidah suaidah Suhadi, Miki Surahman, Ade Suwarni, Emi Syahwaluddin, Risal Taufiq Martiwansyah Tenda, Edwin Wang, Junhai YOHANA TRI UTAMI, YOHANA TRI Yuri Rahmanto Yusra Fernando