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All Journal INTI Nusa Mandiri Jurnal Infortech
Anton
Nusamandiri University
Computer Science & IT Engineering

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Analysis and Implementation of the PCQ Method in MikroTik-Based Bandwidth Management Anton; Mochamad Wahyudi; Corleon Adonay Theofilus; Hendra Supendar; Hilda Amalia; Salman Alfarizi; Lise Pujiastuti
Jurnal Infortech Vol. 8 No. 1 (2026): June 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v8i1.12752

Abstract

This study aims to implement bandwidth management using the Per Connection Queue (PCQ) method on a MikroTik router to overcome uneven bandwidth distribution. The main problem frequently encountered is the lack of optimal network traffic management, which impacts network performance and work productivity. The research method used is the Network Development Life Cycle (NDLC) with data collection techniques through observation, interviews, and literature studies. The analysis results indicate that the network does not yet have a bandwidth management system and priority allocation among departments. The proposed solution is the implementation of Simple Queue combined with the PCQ method to distribute bandwidth fairly according to the needs of each floor or department. The testing results show that the PCQ method can distribute bandwidth more systematically and stably, with achieved bandwidth values close to the predetermined targets, such as the 17th floor achieving 68.97/69.53 Mbps from a target of 70 Mbps. The study concludes that the combination of Simple Queue and PCQ on a MikroTik router is effective in creating fair, measurable, and efficient bandwidth management that supports business activities.
AI-DRIVEN ACADEMIC SCREENING: PENGEMBANGAN SISTEM REVIEWER OTOMATIS BERBASIS AI AGENT Verry Riyanto; Andi Saryoko; Anton; Lia Mazia; Nurmalasari; Tati Mardiana
INTI Nusa Mandiri Vol. 20 No. 2 (2026): INTI Periode Februari 2026
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v20i1.6793

Abstract

An artificial intelligence (AI)-based research proposal submission system is an innovative solution to improve efficiency and transparency in the academic selection process. This study develops a web-based system using the Laravel framework integrated with AI Agent to automatically review the title and abstract of lecturers' research proposals. This system is designed with a hybrid training approach, combining Supervised Learning (labeled data) and Reinforcement Learning from Human Feedback (RLHF), and utilizing Natural Language Processing (NLP) techniques for semantic analysis. The implementation results show that the system is able to evaluate research proposals with high accuracy, including checking title-abstract alignment, identifying problem backgrounds, and assessing originality. The system also provides real-time statistics and evaluation records, supporting more objective decision making. The contribution of the research lies in the use of AI to automate academic processes, reduce the workload of human reviewers, and improve the integrity of the research roadmap
Co-Authors Andi Saryoko Corleon Adonay Theofilus Hilda Amalia Lia Mazia Lise Pujiastuti Mochamad Wahyudi Nurmalasari SALMAN ALFARIZI Tati Mardiana Verry Riyanto