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All Journal Jurnal Computech & Bisnis (e-Journal) Seminar Nasional Informatika (SEMNASIF) Jurnal Penelitian Pendidikan IPA (JPPIPA) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Teknologi Informasi dan Komunikasi Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Anderias Eko Wijaya
Universitas Mandiri
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Library & Information Science Materials Science & Nanotechnology Physics

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Real-Time, Multi-Command Drone Navigation Using a Consumer-Grade EEG-Based SSVEP BCI Wijaya, Anderias Eko; Nurizati, Nurizati; Hermawan, Rian; Suhendra, Muhammad Agung
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 8 No. 1 (2026): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v8i1.295

Abstract

Steady-state visual evoked potential (SSVEP) brain-computer interfaces (BCIs) provide a non-invasive method for hands-free device control. However, their practical applications are limited by reliance on costly laboratory-grade electroencephalography (EEG) systems. This study addresses this gap by designing and evaluating a real-time, six-command SSVEP-BCI for drone navigation using a consumer-grade EEG headset. An adaptive processing pipeline was developed to extract spectral and spatial features, which were classified using Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN) models. Analysis of data from 30 participants revealed that the RF classifier achieved an optimal balance between performance and speed, with a high classification accuracy of 87.24% and a low computational latency of 0.09 seconds, resulting in a high information transfer rate (ITR) of 35.0 bits/min. In contrast, the ANN was insufficiently accurate, and SVM performance was marginal. These findings demonstrate the viability of low-cost, multi-command SSVEP-BCIs for applications in assistive technology, teleoperation, and human-computer interaction.
Canonical Correlation Analysis and Its Extension for SSVEP-based BCI Detection: A Systematic Review Muhamad Agung Suhendra; Iqbal Robiyana; Tedi Sumardi; Ahmad Sofyan Sulaeman; Permono Adi Putro; Nurizati Nurizati; Usep Tatang Suryadi; Anderias Eko Wijaya; Sunanto Ajidarmo; Arief Budiman; M. Faizal Amri
Jurnal Penelitian Pendidikan IPA Vol 10 No 12 (2024): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i12.9844

Abstract

SSVEP-based Brain-Computer Interfaces (BCIs) utilize steady-state visual evoked potentials, which are brain responses triggered by visual stimuli flickering at specific frequencies. Users can focus on these stimuli, allowing the system to interpret their intent based on the brain's electrical activity. This technology has applications in communication for individuals with disabilities, gaming, and neuro-feedback, offering an ultimate means of interaction through thought alone. In this study, systematic literature review was conducted to identify analytical methods for SSVEP spellers with PRISMA method from the eligibility criteria. CCA and its extension become gold-standar method that give excellent performances for SSVEP recognition and signal classification. Some uniques features also found such as MsetCCA, FB-CCA, MF-CCA, TW-CCA, CP-CCA, IIS-CCA, TT-CCA and RLS-CCA. Therefore, we have various options for choosing the best method for recognizing SSVEP from EEG signals based BCI.
SISTEM REKOMENDASI KEPUTUSAN UPGRADE SMARTPHONE MENGGUNAKAN ALGORITMA C4.5 BERBASIS AI Haq, Haris Nizhomul; Ahmad, Hermansyah Nur; Catur, Ryan; Wijaya, Anderias Eko; Udoyono, Kodar; Permana, Eka; Leander, Daud Elia
Jurnal Teknologi Informasi dan Komunikasi Vol 19 No 1 (2026): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v19i1.395

Abstract

The increasing use of smartphones necessitates rational decision-making about device upgrades. Many users upgrade without considering the actual device condition and usage requirements. This study aims to develop an artificial intelligence-based recommendation system to objectively determine smartphone upgrade decisions. The method used is the C4.5 algorithm for classification based on device specifications and usage patterns. The dataset consists of 100 records, including 80 for training and 20 for testing. The results show that the system successfully generates a representative decision tree model. Performance evaluation using a confusion matrix yields an accuracy of 95.00 percent, categorized as excellent. The system is also integrated with AI Gemini to generate narrative explanations from classification results, improving interpretability. The contribution lies in integrating classification algorithms with generative models to produce accurate and informative recommendations. This system provides a practical solution for users to efficiently determine smartphone upgrade needs.
Co-Authors Ade Irfan Ahmad Sofyan Sulaeman Ahmad, Hermansyah Nur Apandi, Jamaludin Arief Budiman Catur, Ryan Dadan Marwan Dadan Marwan, Dadan Dede Sopian Deni Alfian Deni Rahmat G. Eby Syaepudin R. Evi Werdi Utami Fahmi Nugraha, Fahmi Fahru Roji Ishaq Hakim, Muhammad Azizul Haq, Haris Nizhomul Haris Munandar Haris Nurjaman Ibnu Juniar Pamungkas Iqbal Robiyana Jupriyanto . Kodar Udoyono, Kodar Leander, Daud Elia Lukman Maulana M. Faizal Amri Moch. Tohira Abdul Malik Muhamad Agung Suhendra Muhamad Agung Suhendra Nugraha, Luthfy Akmal Nur Imam Iskandar Nurhakim, Muhamad Wilvan Nurizati Nurizati Nurizati Nurizati Permana, Eka Permono Adi Putro Purnama Insan Rian Hermawan Rijal Bani Salam Sukarni Roby Muhromi Rokhman, Febriana Nur Siallagan, Timbo Faritcan Parlaungan Siti Nurlaelah Sobari, Dicky Iskandar Sunendra, Ali Tedi Sumardi Tedi Sumardi Ujang Ahmat Hiddah Usep Tatang Suryadi Wulan Maelia Maspupah