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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Teknologi Informasi dan Komunikasi Jurnal Riset Fisika Indonesia Time in Physics: Journal for Theoretical, Instrumentation, Material-Molecular, and Education Physics Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Iqbal Robiyana
Department Of Physics, Faculty Of Science, Universitas Mandiri, Subang Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Health Professions 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.
A Computational Study of Numerical Integration in Physics Applications Using Trapezoidal and Simpson's Methods Suhendra, Muhamad Agung; Assegaf, Sufiyah; Robiyana, Iqbal; Nurizati
TIME in Physics Vol. 2 No. 2 (2024): September
Publisher : Universitas Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/timeinphys.2024.v2i2p85-95

Abstract

This research conducts a comprehensive evaluation of the efficiency and accuracy of two widely-used numerical integration methods, the Trapezoidal Rule and Simpson's Rule, within the context of solving physics-related problems. The study focuses on four representative cases: the calculation of kinetic energy, the determination of electric field strength, the work done by an ideal gas, and the gravitational potential energy. The performance of these methods is analyzed through key metrics such as convergence behavior, error magnitude, and computational time. The findings reveal that Simpson's Rule consistently delivers higher accuracy compared to the Trapezoidal Rule, especially for functions exhibiting non-linear characteristics. This highlights Simpson's Rule as a preferred method for complex physical problems, while the Trapezoidal Rule remains effective for simpler cases requiring lower computational overhead.
Co-Authors Amri, M. Faizal Anderias Eko Wijaya Assegaf, Sufiyah Muhamad Agung Suhendra Nurizati Nurizati Permana, Roni Permono Adi Putro Suhendra, Muhamad Agung Sulaeman, Ahmad Sofyan Sumardi, Tedi Tedi Sumardi Timbo Faritcan Parlaungan Usep Tatang Suryadi, Usep Tatang