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All Journal JOIN (Jurnal Online Informatika) Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Sandi Rahmadika
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Computer Science & IT

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Security Analysis on the Decentralized Energy Trading System Using Blockchain Technology Sandi Rahmadika; Diena Rauda Ramdania; Maisevli Harika
JOIN (Jurnal Online Informatika) Vol 3 No 1 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i1.207

Abstract

Blockchain turns both currencies and commodities into a digital form without relying on middleman which allows one person to trade with another include trading the renewable energy. Blockchain technology as a secure and low-cost platform to track the billions of eventual transactions in a distributed energy economy has attracted the attention of experts in various fields of science. The current form of centralized energy trading system is still suffering from security concerns, quality of service, and to name a few. A decentralized energy system using blockchain technology allows the parties to create a trading energy transaction via microgrid. The blockchain technology offers the promise of an immutable, single source of truth from multiple sources without a third-party involvement. In this paper, we describe, explore and analyze the prominent implementation of blockchain technology in the energy sector. Furthermore, we analyze the security issues and highlight the performance of several attacks that might be occurred in the proposed system.
Synergistic Disruption: Harnessing AI and Blockchain for Enhanced Privacy and Security in Federated Learning Sandi Rahmadika; Winda Agustiarmi; Ryan Fikri; Kweka, Bruno Joachim
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1392

Abstract

Combining blockchain technology with artificial intelligence (AI) offers revolutionary possibilities for developing strong solutions that capitalize on each technology's own advantages. Blockchain technology makes self-executing agreements possible by enabling smart contracts, which reduce the need for middlemen and increase efficiency by precisely encoding contractual terms in code. By using AI oracles, these contracts can communicate with outside data sources and make well-informed decisions based on actual occurrences. Additionally, there is a lot of potential for improving machine learning and data interchange in terms of privacy, security, and transparency through the integration of blockchain with federated learning. In order to provide accountability and transparency, the blockchain's immutable ledger can painstakingly record every transaction that takes place during the federated learning process, from data submissions to model modifications and remuneration. Participants in federated learning networks also develop trust because of blockchain's transparency and resistance to tampering. Strong participant verification procedures are put in place to strengthen data integrity and model updates, which raises the system's overall reliability. In the end, this chapter examines novel research avenues for combining blockchain technology with federated learning, providing practical methods and strategies to improve transaction security and privacy and opening the door to a new era of reliable and effective machine learning applications.
Pendeteksi Mood Mahasiswa Menggunakan Face Emotion Recognation Dengan Algoritma Haar Cascade Filinia Gusti; Ahmaddul Hadi; Sandi Rahmadika
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 2 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i2.724

Abstract

Facial expressions are primary indicators of human emotions, often providing deeper insights than words (Oliver & Alcover, 2020). This study focuses on Mood as a natural response to past experiences, emphasizing its importance for psychological well-being. Over the past five years, the Covid-19 pandemic has triggered a significant global mental health crisis, affecting facial expressions and leading to varying degrees of depression and anxiety. Generation Z, particularly students, have been severely impacted, experiencing declines in academic abilities such as attention and memory (Qorik et al., 2020; Uswatun et al., 2020).In the educational context, the online learning systems adopted during the pandemic have introduced new challenges for students, including technical issues, lack of direct interaction, and less effective delivery of material, all of which contribute to increased academic stress (Rahmayinita, 2020; Utami et al., 2020). Enhancing the affective aspects of online education is crucial to better simulate face-to-face interactions (Bloom et al., 1984; Marzano & Kendall, 2007). This research aims to detect the Mood of students in online learning environments using advanced technology. The system is designed to assist educators in recognizing the academic stress levels of their students, enabling them to develop more creative and responsive teaching strategies (Zulfikri et al., 2023).
Co-Authors Ahmaddul Hadi Diena Rauda Ramdania Filinia Gusti Kweka, Bruno Joachim Maisevli Harika Ryan Fikri Winda Agustiarmi