Article Per Year (5 Year)
p-Index From 2020 - 2025
3.173
P-Index
This Author published in this journals
All Journal JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information Technology and Computer Science (JOINTECS) Zero : Jurnal Sains, Matematika, dan Terapan INFOKUM Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknologi Informasi dan Komunikasi Syntax: Journal of Software Engineering, Computer Science and Information Technology Instal : Jurnal Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Mathematics and Scientific Computing With Applications Journal of Computer Science and Informatics Engineering Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Ilmiah Teknik Informatika dan Komunikasi Journal Of Informatics And Busisnes Jurnal Ilmiah Research Student
Mhd Ikhsan Rifki
Universitas Islam Negeri Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Instal : Jurnal Komputer

 1 
Sentiment Analysis of Platform X Users on Starlink Using Naive Bayes M. Khalil Gibran; Rifki, Mhd Ikhsan; Hasugian, Abdul Halim; Siahaan, Ahmad Taufik Al Afkari; Afandi Sahputra; Ong, Russell
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.240

Abstract

This research aims to analyze public sentiment towards Starlink through tweets collected using the hashtag "starlink." The data crawling process was successful in collecting 1888 tweets. However, upon checking and processing the data, we reduced the number of valid and relevant tweets to 416. This reduction occurred due to duplicate data and the use of common keywords. We performed sentiment classification using the Naive Bayes model, yielding the following sentiment distribution: We classified 287 tweets (68.99%) as positive, 112 tweets (26.92%) as neutral, and 17 tweets (4.09%) as negative. The model performance evaluation shows good results with a recall of 0.80, precision of 0.90, F1 score of 0.83, and accuracy score of 0.80. The results of this study indicate that the majority of tweets related to Starlink have positive sentiments, indicating a generally favorable public perception of the service. A small proportion of tweets showed neutral and negative sentiments, which can provide valuable input for service improvement. The Naive Bayes model is able to classify sentiment with fairly high accuracy, making it one of the most effective tools for sentiment analysis.
Text Data Security Application Using a Mobile-Based Base64 Algorithm Rifki, Mhd Ikhsan; Muhammad Ezar Raditya; Abdul Halim Hasugian
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.146

Abstract

During the process of sending data or information on a communications network, various types of data and important information related to personal data and identity are often transacted on the network. This can be exploited by irresponsible parties to gain personal gain by duplicating personal data or information. So, protection is needed for data sent via communication networks. According to Law No. 27 of 2022, personal data protection includes all efforts to protect personal data and guarantee the constitutional rights of personal data subjects. Based on this, the research objective is to provide users with options to provide additional security for text data in the form of personal data. The base64 application provides data security by changing plaintext into ciphertext, which has an information structure that is very different from the original form of information. The text data security application using the base64 algorithm was designed using the Unified Modeling Language (UML) system development method. Regarding application development, the framework used is modular. So, with this application, text data has additional data security options to avoid behavior that could be detrimental.
Co-Authors Abdul Halim Hasugian Adha Hasibuan, Aidillia Afandi Sahputra Aidil Akbar Simatupang Aidil Halim Lubis Ali Darta Andilala Aulia, M. Arif Bagas F, Muhammad Dwi Prapita Sari Dysa Handira Fadhillah Lubis, Muhammad Arif Fauzi Kurniawan Gibran, M. Khalil Haikal, Baginda Fikri Harjo, William Lutfir Rahman Harun Al Rasyid Hasibuan, Ainun Mardiah Hasibuan, Bunga Lestari Ikhwan, Ali Ilka Zufria Inneke Putri Julianti, Miranda Khairul Azis Khalil Gibran, M. Lubis, Nur Azizah M. Khalil Gibran Mhd Furqan Muhamad - Alda Muhamad Alda Muhammad Ezar Raditya Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad, Faisal Nasution, Fadhilah Ramadhani Ong, Russell Pulungan, Miftahul Rizky Rambe, M. Riski Andika Rini Halila Nasution Salim Salim Siahaan, Ahmad Taufik Al Afkari SIHOMBING, JULIANA SION Suhardi Suhardi Syamia, Nanda Yusuf Ramadhan Nasution