Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Informatik : Jurnal Ilmu Komputer MULTINETICS Berajah Journal
Bagus Gede Krishna Yudistira
Universitas Pendidikan Ganesha
Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Analisis Komparatif NetSpot dan Ekahau Dalam Optimalisasi Penempatan Access Point di DISDIKPORA Kabupaten Buleleng Darma Putra Purba; Gede Arna Jude Saskara; Bagus Gede Krishna Yudistira
MULTINETICS Vol. 11 No. 02 (2025): MULTINETICS Nopember (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i02.7905

Abstract

Optimal access point (AP) placement is essential to ensure uniform and high-quality WiFi signal coverage, particularly in government institutions such as the Department of Education, Youth, and Sports (DISDIKPORA) of Buleleng Regency. This study aims to analyze and compare the effectiveness of Ekahau AI Pro and NetSpot applications in optimizing AP placement. The research methodology integrates Comparative Analysis, Action Research, and Benchmarking, following a structured process consisting of diagnosis, action planning, action taking, evaluation, and learning. Measurements were conducted through active and passive surveys, with cross-validation performed using WiFi Analyzer as a reference tool. Data were collected based on key parameters: Received Signal Strength Indicator (RSSI), blank spot detection, result consistency, and time efficiency. The results indicate that both applications accurately detected all blank spots. However, Ekahau AI Pro demonstrated higher consistency, with only a 1.5 dBm deviation, making it well-suited for long-term planning in complex building environments, despite requiring more time and higher costs. In contrast, NetSpot delivered sufficiently accurate results with an average difference of 6.75 dBm and significantly faster execution time, making it ideal for rapid network audits under limited budgets. Based on the findings, Ekahau AI Pro is recommended for complex environments demanding high accuracy, while NetSpot is more appropriate for fast, dynamic, and cost-effective assessments. This study provides technical recommendations for WiFi network optimization at DISDIKPORA and offers strategic guidance for selecting suitable network mapping tools in similar organizations.
OPTIMASI PENJADWALAN TUGAS CLOUD MENGGUNAKAN ALGORITMA HYBRID GA-PSO: ANALISIS MAKESPAN BERBASIS CLOUDSIM Puguh Setiyono; Bagus Gede Krishna Yudistira
Berajah Journal Vol. 6 No. 4 (2026): Berajah Journal
Publisher : CV. Lafadz Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/bj.v6i4.692

Abstract

Task scheduling is a critical component in cloud computing to ensure optimal resource allocation and execution time. This study proposes a hybrid algorithm that combines Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to minimize makespan in cloud task scheduling. The algorithm leverages the global exploration capability of GA and the local exploitation strength of PSO. The simulation was conducted using CloudSim 3.0.3 with three different workload scenarios: light, medium, and heavy. Each configuration varied in terms of cloudlet count, virtual machines, CPU capacity, task length, and memory allocation. Results indicate that the hybrid GA–PSO algorithm consistently outperformed standalone GA and PSO in minimizing makespan, particularly under heavy workloads. It achieved an 11.0% reduction compared to GA and 22.3% compared to PSO. Moreover, the hybrid approach demonstrated greater stability and adaptability in constrained resource environments. These findings support the practical use of the hybrid GA–PSO algorithm in dynamic cloud systems and highlight its potential for future development in multi-objective optimization and real-world deployments.
Analisis Komparatif Efektivitas Client-Side Encryption Cryptomator dan Rclone Crypt pada Google Drive I KOMANG WAHYU AMBARA PUTRA AMBARA; Bagus Gede Krishna Yudistira
Informatik : Jurnal Ilmu Komputer Vol 21 No 2 (2025): Agustus 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i2.11801

Abstract

Penggunaan cloud storage seperti Google Drive yang semakin masif dihadapkan pada tantangan keamanan data. Client-Side Encryption (CSE) menjadi solusi penting untuk melindungi privasi pengguna, namun studi komparatif mengenai efektivitas perangkat lunak CSE masih terbatas. Penelitian ini melakukan analisis komparatif dengan pendekatan eksperimental untuk mengevaluasi efektivitas enkripsi client-side Cryptomator dan Rclone Crypt. Analisis mencakup parameter kinerja seperti kecepatan enkripsi dan unggah data, perubahan ukuran file, visibilitas metadata, aksesibilitas, portabilitas, dan kecepatan unduh data. Hasil pengujian menunjukkan Rclone Crypt secara konsisten dan signifikan secara statistik lebih unggul dalam hal kecepatan proses dan overhead ukuran file kurang dari setengah yang dihasilkan Cryptomator. Sebaliknya, Cryptomator menawarkan kemudahan penggunaan dan portabilitas yang lebih superior bagi pengguna umum, serta mampu menyamarkan struktur folder secara total untuk privasi yang lebih baik. Kesimpulan utama dari penelitian ini adalah adanya trade-off fundamental antara performa dan kemudahan penggunaan. Rclone Crypt direkomendasikan untuk pengguna teknis yang memprioritaskan kecepatan dan efisiensi, sedangkan Cryptomator menjadi solusi yang lebih tepat bagi pengguna non-teknis yang mengutamakan kesederhanaan dan privasi struktural. Penelitian ini memberikan panduan praktis bagi pengguna untuk memilih solusi CSE yang sesuai dengan kebutuhan teknis dan preferensi pengguna.
Co-Authors Darma Putra Purba Gede Arna Jude Saskara I KOMANG WAHYU AMBARA PUTRA AMBARA Puguh Setiyono