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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic AMMA : Jurnal Pengabdian Masyarakat
Prastika Indriyanti
Universitas Mercu Buana
Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Pelatihan Pembuatan Daftar Pustaka Menggunakan Aplikasi Mendeley Arafat Febriandirza; Prastika Indriyanti
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 : Juli (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Many students struggle with manually creating bibliographies for their academic papers, a crucial step to prevent plagiarism. The Mendeley application offers a solution by automatically generating reference lists, yet not all students are familiar with it. Therefore, an online training session was held via Zoom for the general student population. The goal was to equip them with practical knowledge and skills in using Mendeley, enabling them to manage references independently for various academic writings such as journals and theses. This training is expected to not only enhance individual competencies but also contribute to improving the quality of education in Indonesia.
Energy-Aware Multi-Objective Deployment Optimization of Wireless Sensor Networks Using Direct Radio Graph Medium (DRGM) Modelling Fandi Ali Mustika; Ali Herdian; Prastika Indriyanti; Muhammad Rifqi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 14 No. 1 (2026): March 2026
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v14i1.12233

Abstract

Wireless Sensor Networks (WSNs) are widely deployed for large-scale environmental monitoring applications, particularly in remote and maritime areas where manual surveillance is costly and impractical. One of the major challenges in WSN deployment is achieving full sensing coverage and network connectivity while minimizing energy consumption and deployment density. This paper proposes an energy-aware multi-objective deployment optimization model based on Direct Radio Graph Medium (DRGM) modeling. The deployment problem is formulated as a multi-objective optimization task aiming to minimize the number of active sensor nodes while maintaining communication connectivity under predefined sensing and transmission constraints. A genetic algorithm–based optimization mechanism is employed to generate Pareto-optimal deployment solutions. The proposed model is evaluated using NS-2 simulations under various node densities and traffic rates. Simulation results show that the DRGM-based deployment achieves full coverage using only 10 sensor nodes, compared to 50–100 nodes in random deployment, corresponding to a node reduction of up to 90%. Furthermore, the proposed approach significantly reduces network power consumption and radio duty cycles, demonstrating its effectiveness for energy-efficient and scalable WSN deployment in large monitoring areas.
Co-Authors Ali Herdian Fandi Ali Mustika Febriandirza, Arafat Muhammad Rifqi