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All Journal International Journal of Applied Mathematics and Computing. International Journal of Electrical Engineering, Mathematics and Computer Science
Tatinia Arda Rizqi Amalia
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Computer Science & IT Engineering Mathematics

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Optimization of Signature Language Tracking Objects Using GMM Models and Kalman Filters Including ROI Dadang Iskandar Mulyana; Sopan Adrianto; Tatinia Arda Rizqi Amalia; Putri Elsa Widiastuti
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 1 No. 3 (2024): September : International Journal of Electrical Engineering, Mathematics and Co
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v1i3.7

Abstract

Sign language recognition is one of the areas of image recognition and image processing technology that is developing rapidly in human-computer interaction. This technology really helps the deaf and speech impaired in communicating with non-disabled people. This research aims to examine the optimization of an object tracking system in sign language using the Gaussian Mixture Model (GMM) and Kalman Filter by including the Region of Interest (ROI). The proposed system consists of three main components, namely hand detection, object extraction, and classification. Hand detection is done using the Kalman Filter to track hand movements accurately. Next, Region of Interest (ROI) features, such as shape, direction and movement features, are extracted from the detected part of the hand. These features are fed into a Gaussian Mixture Model (GMM) classifier, which can recognize sign language based on the extracted features. With the combination of GMM and Kalman Filter in this research, it can increase accuracy in object tracking, reduce interference from the background, and ensure the tracking focus remains on important objects. The dataset used is in the form os SIBI alphabet symbols, namely A-Z with the amount of data for each class, namely 620 images. Based on the research result, model testing using GMM, Kalman Filter and ROI produces higher accuracy of 99%, while model testing using GMM and ROI produces accuracy of 90%.
Optimizing Bandwidth Settings Using the Y.1731 Method Based on Ethernet OAM on Raisecom Devices in a Metro Ethernet Network Dadang Iskandar Mulyana; Nandang Sutisna; Tatinia Arda Rizqi Amalia; Muhamad Rafli Alfiansyah
International Journal of Applied Mathematics and Computing Vol. 2 No. 4 (2025): October : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i4.283

Abstract

The rapid development of network infrastructure demands high Quality of Service (QoS), especially in Metro Ethernet networks widely utilized by telecommunication service providers. A primary challenge is efficient bandwidth management to ensure network stability and performance. This research aims to optimize bandwidth management by implementing the Y.1731 method based on Ethernet Operations, Administration, and Maintenance (OAM) on Raisecom devices. The methodology employed is a quantitative experimental approach based on technical simulation within an Professional Network Emulator Tool Lab (PNET Lab), where real-time network performance measurements are conducted using the ITU-T Y.1731 protocol for key parameters such as delay, jitter, and packet loss on Raisecom devices (represented by Cisco routers). The expected outcomes include increased efficiency in bandwidth utilization through more adaptive allocation, comprehensive and accurate real-time network performance monitoring capabilities, validation of OAM functions on Raisecom devices, improved Quality of Service (QoS) and better Service Level Agreement (SLA) attainment, and the provision of technical recommendations for network management. The implementation of Y.1731 is anticipated to quickly detect and respond to service degradation, thereby providing a strong basis for decision-making in network management and contributing to the enhancement of service quality in Metro Ethernet networks through optimization based on proactive monitoring.
Co-Authors Dadang Iskandar Mulyana` Muhamad Rafli Alfiansyah Nandang Sutisna Putri Elsa Widiastuti SOPAN ADRIANTO