https://jurnal.uniraya.ac.id/index.php/JI/issue/feed Jurnal Informatika 2025-05-13T21:51:28+07:00 Firdaus Laia firdauslaia@uniraya.ac.id Open Journal Systems <p align="justify">Journal of Informatics is a scientific journal focused on research and studies in the fields of computer science, information systems, and information technology. The journal aims to provide a platform for researchers, academics, and practitioners to share their research findings, innovations, and the latest insights in these fields. It is published by LPPM Universitas Nias Raya with a biannual publication schedule in March and September.</p> https://jurnal.uniraya.ac.id/index.php/JI/article/view/2554 Perancangan Sistem Informasi Penjualan Online dan Evaluasi Penerimaan Teknologi Menggunakan Model TAM pada Toko Sepatu XYZ 2025-05-13T21:51:28+07:00 Nurul Fajriyah nurulfajriyah442@gmail.com Wawan Setiawan whawan.s@gmail.com Tobias Duha bungtd@uniraya.ac.id <p><em>The development of information technology in the current digital era encourages various sectors to enhance efficiency, competitiveness, and service reach through digital transformation. One form of its implementation is the development of online product sales systems. Toko XYZ, a business engaged in shoe sales, still relies on conventional sales methods through physical stores, thus facing challenges in reaching a wider range of customers amid changing consumer behavior. This study aims to develop a website-based sales system to support the digitalization of business operations at Toko XYZ. Data collection methods included observation, interviews, and literature studies to identify system requirements. The developed e-commerce website is designed to expand market reach, facilitate transaction processes, and provide a more convenient shopping experience for customers. System evaluation was carried out using the Technology Acceptance Model (TAM) approach, with measurements conducted through a Likert scale-based questionnaire. Analysis results show that the user acceptance rate for the website reached 89%, which falls into the "strongly agree" category. These findings indicate that the implementation of a website-based online sales system can improve sales effectiveness, expand the customer base, and strengthen Toko XYZ's competitive position in the digital market.</em></p> 2025-03-30T00:00:00+07:00 Copyright (c) 2025 Nurul Fajriyah, Wawan Setiawan, Tobias Duha https://jurnal.uniraya.ac.id/index.php/JI/article/view/2574 Analisis Sentimen Pengguna Twitter terhadap Konflik Rusia-Ukraina Menggunakan Naïve Bayes dan Lexicon Based Features 2025-05-13T21:50:22+07:00 Barnes J. Manurung barnes.manurung@gmail.com Bita Parga Zen bita.parga@machung.ac.id Yohani Setiya Rafika Nur yohani@telkomuniversity.ac.id Roland Claudio Felle rolandfelle14@gmail.com Eryan Ahmad Firdaus eryan.firdaus@idu.ac.id <p><em>The conflict between Russia and Ukraine remains one of the major international issues drawing global attention. It began in 2014 with the ousting of President Yanukovych, which triggered a political divide between pro-European Union and pro-Russian factions within Ukraine. Tensions escalated significantly by late 2021, culminating in Russia’s military aggression against Ukraine on February 24, 2022, under President Vladimir Putin’s directive. Twitter, as a social media platform, became a major outlet for the public to express their opinions regarding the conflict. This study aims to analyze public sentiment on Twitter concerning the Russia-Ukraine conflict. The methods used in this research are a combination of the Naïve Bayes algorithm and Lexicon Based Features. Naïve Bayes is utilized to classify sentiment data, while Lexicon Based Features assign weights to positive and negative sentiment words in textual data. The results show that this combined method is effective in categorizing public opinions based on their sentiments towards the conflict. This sentiment analysis provides a broader understanding of global perceptions and may serve as a reference for assessing public opinion in digital media contexts.</em></p> 2025-03-30T00:00:00+07:00 Copyright (c) 2025 Barnes J. Manurung, Bita Parga Zen, Yohani Setiya Rafika Nur, Roland Claudio Felle, Eryan Ahmad Firdaus