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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal Software Engineering and Computer Science (IJSECS)
Nandang Sutisna
Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Optimization of Bandwidth Management Using Y.1731 Method Based on Ethernet OAM on Raisecom Devices in Metro Ethernet Networks Muhamad Rafli Alfiansyah; Nandang Sutisna
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5418

Abstract

The growing demand for reliable Quality of Service (QoS) in Metro Ethernet networks has highlighted the need for a bandwidth management approach that is both standardized and efficient. This research explores the optimization of bandwidth configuration through the implementation of the ITU-T Y.1731 protocol, which operates within the framework of Ethernet Operations, Administration, and Maintenance (OAM). A network simulation was carried out using the Enterprise Network Simulation Platform (eNSP) with Huawei devices, serving as a functional equivalent of Raisecom equipment. The study employed a quantitative experimental method, involving the design and configuration of a Metro Ethernet topology, the deployment of Connectivity Fault Management (CFM), and the activation of performance monitoring mechanisms such as Delay Measurement Message (DMM) and Loss Measurement Message (LMM). Key performance indicators analyzed included delay, jitter, and packet loss, observed before and after the Y.1731 implementation. The findings reveal that the application of Y.1731 improved bandwidth utilization efficiency by up to 25%, reduced average delay, minimized jitter, and produced measurable data for validating Service Level Agreement (SLA) compliance. Overall, the integration of Y.1731 into Metro Ethernet networks based on Huawei devices demonstrates a practical and effective solution for strengthening service performance and ensuring network reliability.
Prediksi Motif Batik dengan Menggunakan Metode Gabor Filter Convolution Neural Network Yudisman Ferdian Bili; Tundo; Nandang Sutisna; Atsilah Daini Putri; Dita Tri Yuliantoro; Laily Nurmayanti
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3798

Abstract

This research aims to develop a batik motif classification system by utilizing Convolutional Neural Network (CNN) and Gabor Filter, in order to increase accuracy in texture feature extraction. The batik dataset used goes through a preprocessing stage, which includes normalization and data augmentation. During training, the model was tested with 10,000 iterations, using the Adam optimizer and the Categorical Cross-Entropy loss function, and evaluated via a confusion matrix. Test results show accuracy reaching 87%, with a precision and recall value of 90% each, and an F1-score of 89%. This method has proven effective for classifying batik motifs and has the potential to be applied in the fields of education, textile industry and cultural preservation.
Co-Authors Atsilah Daini Putri Dita Tri Yuliantoro Laily Nurmayanti Muhamad Rafli Alfiansyah Tundo Yudisman Ferdian Bili