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Peningkatan Kapasitas Digital Pengelola BLK Komunitas Al-Barkah melalui Pelatihan dan Pengembangan Website di Lebakmuncang Ciwidey Robin Sinurat; Naufal Hanan Lutfianto; Linda Meylani
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 5 No. 1 (2025): The Proceeding of Community Service and Engagement (COSECANT) Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v5i1.9372

Abstract

Pengembangan sistem informasi berbasis web merupakan kebutuhan esensial bagi institusi pendidikan dan pelatihan, termasuk Balai Latihan Kerja Komunitas (BLKK), sebagai sarana peningkatan efektivitas komunikasi, pelayanan, dan eksistensi di era digital. BLKK AL-Barkah Lebakmuncang merupakan salah satu lembaga yang tidak hanya fokus pada peningkatan keterampilan anggota, tetapi juga berperan dalam optimalisasi potensi sumber daya lokal guna mendukung perekonomian masyarakat sekitar. Namun, hingga saat ini, BLKK AL-Barkah belum memiliki website sebagai media informasi dan promosi, sehingga informasi terkait program pelatihan, inovasi, dan kreativitas sulit diakses oleh masyarakat luas. Pengabdian masyarakat ini bertujuan untuk merancang dan mengembangkan website BLKK AL-Barkah menggunakan metode Waterfall guna menghasilkan antarmuka yang ramah pengguna serta fitur-fitur yang mendukung penyebaran informasi pelatihan secara digital. Hasil kegiatan menunjukkan adanya peningkatan pemahaman stakeholder terhadap penggunaan website sebesar 23%, yang mengindikasikan efektivitas pelatihan dalam meningkatkan literasi digital peserta. Diharapkan ke depannya, BLKK AL-Barkah mampu secara mandiri mengelola dan memanfaatkan website sebagai media informasi dan promosi kegiatan pelatihan.
Resource Block Allocation: Performance Comparison of Auction, Greedy, and Round Robin Algorithms Kahyangan, Fortuna; Fakhrudin, Muhammad Harits; Furqan, Revin Abyan; Meylani, Linda; Prabowo, Vinsensius Sigit Widhi
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 01 (2026): May 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v3i02.8025

Abstract

Heterogeneous Networks (HetNets) that integrate Wi-Fi, 4G, and 5G technologies present significant challenges in resource management and power allocation. This study evaluates the performance of resource block (RB) allocation in a two-level HetNet model consisting of one macro cell base station (MBS) and four small cell base stations (SBS). Utilizing K-Medoids clustering, allocations are analyzed under various conditions using Greedy, Auction, and round robin algorithms. Simulations reveal that the Greedy algorithm outperforms the Auction and round robin algorithms in optimizing data rate, sum rate, spectral efficiency, power efficiency, and fairness. Specifically, the Greedy algorithm achieves an average data rate of 1.642 bps, an average sum rate rate of 1.218 bps, an average spectral efficiency of 3.046 bps/Hz, an average power efficiency of 1.650 bps/W, and an average fairness of 0.329, indicating its effectiveness in improving HetNet performance.
Performance Optimization of Greedy and FIFO Algorithm In Vehicle to Vehicle (V2V) Communication Dharmawan, Muhammad Raditya 'Aisy; Cahaya, Muhammad Satrio Dwi; Winata, Raffie Ilham; Meylani, Linda; Prabowo, Vinsensius Sighit Widhi
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 01 (2026): May 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v3i02.8031

Abstract

In the era of autonomous vehicles, Vehicle-to-Vehicle (V2V) communicationis crucial for enhancing traffic efficiency. This study adheres to the standardsof 3GPP TS 22.185, TS 22.186, TS 22.885, and TS 22.886 to support V2Xcommunication in 5G networks. We evaluated the resource allocationalgorithms FIFO and Greedy, using both clustering and non-clusteringapproaches. The test results indicate that the Greedy algorithm withclustering outperforms FIFO. In the first scenario, Greedy with clusteringimproves the Total Data Rate by 8.97%, the Average Data Rate by 10.08%,and the Spectral Efficiency by 9.09%. In the second scenario, there is anincrease in the Total Data Rate by 11.07%, the Average Data Rate by 7.91%,and the Spectral Efficiency by 10.57%. This study recommends using theGreedy algorithm with clustering for optimizing radio resource allocationperformance in V2V communication, as it demonstrates higher values andperformance improvements compared to the FIFO algorithm with clustering.