Sestri Novia Rizki
Universitas Media Nusantara Citra, Indonesia

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Development of Sustainable Curriculum Management System with Server-Driven Go and Next.js Adi Fitrianto; Farel Artanto Kangadi; Sestri Novia Rizki; Verra Budhi Lestari; Eko Amri Jaya
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.5381

Abstract

Curriculum management is a crucial aspect of educational administration, encompassing the planning, organization, and continuous updating of course data and curriculum structures. In many educational institutions, including those in Jakarta, this process still encounters challenges such as inefficiency, data duplication, inconsistent information flow, and high system maintenance overhead. These issues often result in delays, administrative burdens, and reduced productivity. This research aims to develop a sustainable curriculum management system by leveraging Go technology on the backend and Next.js on the frontend, adopting a server-driven approach to minimize processing loads on client devices, improve resource efficiency, and ensure faster data delivery. The system development method employs an iterative approach with the integration of ten supporting technologies, including server-side data fetching, Backend for Frontend (BFF), OpenAPI 3 with code generation, Redis caching, tag-based revalidation, Server-Sent Events (SSE), component-based UI, image optimization, and asynchronous job queues for heavy tasks. The system integrates course and curriculum name management into a single, responsive, secure, and easily extensible platform. Implementation results demonstrate that the approach can reduce maintenance complexity, improve data consistency, and significantly enhance application response time under varying loads. Furthermore, the system supports sustainable software engineering principles, enabling scalability and adaptability to future needs. Consequently, it offers an effective, long-term solution for curriculum management, contributing to operational efficiency and the overall quality of academic administration in educational institutions across Jakarta.
Smart Tourism In Padang: Minangkabau Cultural And Gastronomic Recommendations Using Best First Search Eko Amri Jaya; Fabriano Saptodewo; Anintyo Herdadi; Sestri Novia Rizki; Adi Fitrianto; Wida Nofiasari
Brilliance: Research of Artificial Intelligence Vol. 6 No. 4 (2026): Brilliance: Research of Artificial Intelligence, Article Research November 2026
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v6i4.9479

Abstract

The city of Padang possesses significant tourism potential, driven by its wealth of natural attractions, Minangkabau culture, and distinctive gastronomy all of which serve as major draws for visitors. However, existing tourism information remains fragmented across various platforms, lacks systematic integration, and fails to provide destination recommendations tailored to user preferences. This situation hinders the implementation of "smart tourism," which requires intelligent, adaptive, and data-driven information systems. This study aims to develop a tourism recommendation model that integrates Padang's tourist destinations, culture, and gastronomy using the Best-First Search algorithm to generate recommendations that are more relevant, efficient, and aligned with traveler needs. The research employs an applied methodology comprising several stages: identifying and classifying data on tourist destinations, culture, and gastronomy; designing a recommendation model based on the Best-First Search algorithm; implementing the system; and testing and evaluating the model's performance using a dataset of Padang's tourist attractions. The results demonstrate that the developed model successfully integrates tourism information in a structured manner and generates destination recommendations that match user preferences based on selected criteria. Furthermore, the Best-First Search algorithm accelerates the process of finding optimal recommendation routes, thereby offering the potential to support the development of smart tourism services that are more effective, interactive, and focused on the visitor experience in Padang.