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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Indonesian Journal on Computing (Indo-JC) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Artificial Intelligence and Data Mining Building of Informatics, Technology and Science eProceedings of Engineering Telkatika: Jurnal Telekomunikasi Elektro Komputasi & Informatika
Prasti Eko Yunanto
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science

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Journal : indonesian journal on computing indo-jc

 1 
Column-Level Database Encryption Using Rijndael Algorithm and Dynamic Key on Learning Management System Ariva Syam Mursalat; Ari Moesriami Barmawi; Prasti Eko Yunanto
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.609

Abstract

The course management system’s goal is to help learning activities. The system helps tomanage tasks, the grading process, and user communications. To avoid unauthorized dataaccess, the course management system needs a mechanism to protect the password that isused in the system’s login process. Database encryption using Rijndael algorithm is proposedby Francis Onodueze et al. to protect the data. A key is needed for the encryption process,and the key has to be kept secret. Thus, when the key is static, it is vulnerable against keyguessing attacks. To overcome the static key’s drawback, a dynamic key generation usingHash Messages Authentication Code - Deterministic Random Bit Generator (HMAC-DRBG)is proposed because it can generate keys periodically. Based on the evaluation, the probabilityof success key guessing attack using the proposed method is less than using the previousmethod, while the time complexity of those methods is similar.
Public Perception of Buying and Selling Bitcoin Using Lexicon Sentiment Analysis Muhammad Rahman Ali; Wijaya, Rifki; Yunanto, Prasti Eko
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.980

Abstract

This study investigates public perceptions of Bitcoin (BTC) trading using sentiment lexicon analysis. The rapid growth of cryptocurrency trading has attracted significant public interest and investment, making it crucial to understand the sentiments and opinions surrounding BTC transactions. By employing sentiment lexicon methods, this research analyzes tweets and social media posts to determine public sentiment. The study aims to identify trends and patterns in public opinion, providing insights into how sentiment impacts BTC trading behavior. Preliminary results indicate a correlation between positive sentiment and increased trading activity, while negative sentiment correlates with market declines. This research contributes to a better understanding of the role of public sentiment in the volatile cryptocurrency market.
Public Perception of Buying and Selling Bitcoin Using Lexicon Sentiment Analysis Muhammad Rahman Ali; Wijaya, Rifki; Yunanto, Prasti Eko
Indonesian Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.980

Abstract

This study investigates public perceptions of Bitcoin (BTC) trading using sentiment lexicon analysis. The rapid growth of cryptocurrency trading has attracted significant public interest and investment, making it crucial to understand the sentiments and opinions surrounding BTC transactions. By employing sentiment lexicon methods, this research analyzes tweets and social media posts to determine public sentiment. The study aims to identify trends and patterns in public opinion, providing insights into how sentiment impacts BTC trading behavior. Preliminary results indicate a correlation between positive sentiment and increased trading activity, while negative sentiment correlates with market declines. This research contributes to a better understanding of the role of public sentiment in the volatile cryptocurrency market.
Co-Authors Aditya Firman Ihsan Aji Gautama Putrada Alhafidz, Bagas Millen Arfive Gandhi Ari Moesriami Barmawi Ariva Syam Mursalat Azzam, Muhammad Abdullah Donni Richasdy Ema Rachmawati Fadhlurrahman Akbar Nasution Faturahman, Farhan Febryanti Sthevanie Gamma Kosala Hertog Nugroho Hutomo, Ardityo Cahyo Putro Hutomo I NYM Yoga Saputra I Wayan Krisna Gita Santika Kurniawan Nur Ramadhani Larasati Larasati Mahmud Dwi Sulistiyo Maulana, Didit Johar Muhamad Fariz Maulana Muhammad Rahman Ali Redy Indrawan Richasdy, Donny Ridlo Yanuar Rifki Wijaya Riski Novanda Sabrina Adinda Sari Sailellah, Hassan Rizky Putra Siti Sa'adah Siti Saadah Siti Saadah Siti Sa’adah Siti Sa’adah Tjokorda Agung Budi Wirayuda Untari Novia Wisesty