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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Time in Physics: Journal for Theoretical, Instrumentation, Material-Molecular, and Education Physics
Suhendra, Muhamad Agung
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Mathematics Physics

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Object Tracking Based on Camera Using Anfis and Fuzzy Classifier for RGB Color Iqbal Robiyana; Timbo Faritcan Parlaungan; Sarifudin; Suhendra, Muhamad Agung
TIME in Physics Vol. 1 No. 2 (2023): August
Publisher : Universitas Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/timeinphys.2023.v1i2p85-91

Abstract

Image processing technology has a wide range of applications, such as in the medical, military, surveillance, and robotics industries. Analyzing objects in images is crucial when it comes to image processing. This study focuses on image processing to track objects of red, green, and blue (RGB) colors through the utilization of a camera. There are two research schemes: image processing and data classification. The data classification method used is the fuzzy and adaptive neuro-fuzzy inference system (ANFIS). The methods of image subtracting and region properties are commonly utilized for image processing. Based on the classification data results, the fuzzy logic classification demonstrated a higher accuracy rate of 86% when compared to Anfis' 65%. This was observed when both classification models were tested using a random sample. The value of Anfis is small due to the limited size of the training data used. As a result, it is recommended to use a fuzzy classifier for object color tracking for good performance.
Canonical Correlation Analysis and Its Extension for SSVEP-based BCI Detection: A Systematic Review Suhendra, Muhamad Agung; Robiyana, Iqbal; Sumardi, Tedi; Sulaeman, Ahmad Sofyan; Putro, Permono Adi; Nurizati, Nurizati; Suryadi, Usep Tatang; Wijaya, Anderias Eko; Ajidarmo, Sunanto; Budiman, Arief; Amri, M. Faizal
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.
Co-Authors Amri, M. Faizal Arief Budiman Iqbal Robiyana Muhamad Agung Suhendra Nurizati Nurizati Permono Adi Putro Sulaeman, Ahmad Sofyan Sumardi, Tedi Tedi Sumardi Timbo Faritcan Parlaungan Usep Tatang Suryadi, Usep Tatang