Edy Yuliansyah, Muhammad Nabil Hatami, Mohammad Reza Fahlevi

IMPLEMENTASI QUEUE TREE DAN MANGLE UNTUK OPTIMALISASI JARINGAN BERBASIS MIKROTIK DI LINGKUNGAN UNIVERSITAS NAHDLATUL ULAMA INDONESIA

Introduction

Implementasi queue tree dan mangle untuk optimalisasi jaringan berbasis mikrotik di lingkungan universitas nahdlatul ulama indonesia. Optimalkan jaringan universitas dengan MikroTik Queue Tree & Mangle. Atasi distribusi bandwidth tak merata, prioritaskan layanan akademik, dan tingkatkan kualitas akses internet di UNU Indonesia.

Abstract

Kebutuhan akan koneksi jaringan internet yang stabil dan efisien semakin meningkat, terutama di lingkungan perguruan tinggi yang mengandalkan layanan daring untuk kegiatan akademik dan administrasi. Permasalahan umum yang sering terjadi adalah distribusi bandwidth yang tidak merata, tidak adanya pemisahan trafik berdasarkan prioritas layanan, serta lemahnya manajemen trafik data. Universitas Nahdlatul Ulama Indonesia menghadapi kondisi tersebut, di mana pengguna jaringan mengalami penurunan kualitas akses terutama pada jam-jam sibuk. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem manajemen bandwidth berbasis MikroTik dengan memanfaatkan fitur Queue Tree dan Mangle. Metode penelitian yang digunakan adalah pendekatan PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize), yang memungkinkan penerapan sistem jaringan yang sistematis dan berkelanjutan. Fokus penelitian ini adalah pada proses penandaan trafik dan pengaturan alokasi bandwidth berdasarkan jenis layanan, sehingga layanan prioritas seperti sistem informasi akademik dan pembelajaran daring dapat berjalan dengan lebih optimal. Penelitian ini juga melibatkan pengujian parameter kualitas layanan jaringan Quality of Service dan pengumpulan data persepsi pengguna terhadap perubahan performa jaringan setelah implementasi sistem.

Review

The paper "IMPLEMENTASI QUEUE TREE DAN MANGLE UNTUK OPTIMALISASI JARINGAN BERBASIS MIKROTIK DI LINGKUNGAN UNIVERSITAS NAHDLATUL ULAMA INDONESIA" addresses a pertinent issue of network inefficiency and instability within academic institutions, specifically at Universitas Nahdlatul Ulama Indonesia. It highlights common challenges such as uneven bandwidth distribution, absence of traffic prioritization, and inadequate data traffic management, which are exacerbated during peak hours. This problem is highly relevant given the increasing reliance on stable and efficient internet connectivity for critical academic and administrative online services in modern universities. To tackle these issues, the research proposes the design and implementation of a MikroTik-based bandwidth management system utilizing Queue Tree and Mangle features. The methodology adopted is the PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) approach, signifying a structured and sustainable path for network system deployment. A key focus of the study is on intelligent traffic marking and subsequent bandwidth allocation based on service type, with a clear objective to prioritize essential services like academic information systems and online learning platforms. The abstract also indicates a robust evaluation plan, involving Quality of Service (QoS) parameter testing and the collection of user perception data to assess the practical impact of the implemented system. This study holds significant practical implications for enhancing network performance and user experience within the specified university environment and potentially for other similar institutions facing comparable network challenges. The systematic approach promised by the PPDIOO methodology, combined with the targeted application of MikroTik's powerful features, suggests a well-considered solution. To fully demonstrate its contribution, the forthcoming paper should provide detailed results of the QoS metrics, a thorough analysis of the user perception data, and a discussion on the achieved improvements in network stability and efficiency for prioritized services, thereby solidifying the effectiveness of the proposed optimization strategy.

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