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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Muhammad Alfath Frandhana Sihotang
Universitas Malikussaleh
Computer Science & IT Engineering

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SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN FRAMEWORK WEB MENGGUNAKAN METODE WEIGHTED PRODUCT: DECISION SUPPORT SYSTEM FOR WEB FRAMEWORK SELECTION USING WEIGHTED PRODUCT METHOD Muhammad Alfath Frandhana Sihotang; Fadlisyah; Fajriana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.6610

Abstract

There are many types of web frameworks available today, each with its own characteristics, advantages, and limitations. This diversity often makes it difficult for developers to determine the most appropriate framework to meet all project needs. This study aims to help developers determine the best framework that can be used optimally on small and large-scale projects. The research process includes determining framework selection criteria based on literature studies, assessing the weight of criteria from developers and students, and collecting framework data through online platforms such as Official Documentation (official websites of the frameworks studied), Github, and Stack Overflow. Based on the results of the analysis and evalution of the collected data, it was found that the Next.js framework ranked highest as the best front-end framework with a final score of 0.04566 on a scale of 0-1, and the FastAPI framework ranked highest as the best back-end framework with a final score of 0.04385 on a scale of 0-1. Thus, Next.js (front-end framework) and FastAPI (back-end framework) are considered to have superior performance, high scalability, and extensive community support, making it easier for developers to find solutions, documentation, and development references. If an error or bug occurs, developers can ask questions on the Github website, Stack Overflow and the Official Documentation of the framework.  
Co-Authors Fadlisyah Fajriana, Fajriana