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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan
Rendyka Purnama
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Aerospace Engineering Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences

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Penerapan Metode SMART Dalam Menentukan Aplikasi Pesan-Antar Terbaik Arief Febrian; Matheos Oktavio Selan; Rendyka Purnama; Rifqi Surya Bernada; Perani Rosyani
AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Vol. 1 No. 3 (2023): Jurnal AI dan SPK : Jurnal Artificial Inteligent dan Sistem Penunjang Keputusan
Publisher : CV. Shofanah Media Berkah

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Abstract

Jurnal ini membahas penerapan Metode SMART dalam menentukan aplikasi pesan-antar terbaik, dengan fokus pada JNE, J&T, TIKI, dan SiCepat. Kriteria evaluasi yang digunakan melibatkan Biaya Pengiriman, Kecepatan Pengiriman, Keamanan Pengiriman, Pelacakan Pengiriman (Tracking), dan Ketersediaan Layanan Pick-Up. Bobot nilai untuk setiap kriteria ditetapkan dalam rentang 1-5, dengan nilai 1 untuk Sangat Buruk, 2 untuk Buruk, 3 untuk Cukup, 4 untuk Baik, dan 5 untuk Sangat Baik. Sistem penunjang keputusan digunakan untuk memproses data dan memberikan rekomendasi berdasarkan nilai yang diperoleh. Metode SMART (Simple Multi-Attribute Rating Technique) diterapkan untuk menyederhanakan proses pengambilan keputusan. Hasil penelitian ini memberikan rekomendasi mengenai aplikasi pesan-antar terbaik berdasarkan kriteria yang telah ditetapkan.
Pengembangan Platform Digital Komunitas Alumni Universitas Al-Azhar Berbasis Web Menggunakan Nextjs dan Prisma ORM Rendyka Purnama; Wasis Haryono
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

This report presents the development of a web-based digital platform for the alumni community of Al-Azhar University using Next.js and Prisma ORM. The project addresses the lack of an official, centralized channel for alumni data management, communication, and professional networking, which has relied on unstructured social media. The objective is to design and implement a system that facilitates alumni connections, centralizes alumni records, and provides professional features such as discussion forums, profile management, and an administrative dashboard. The methodology includes observation and interviews, system design (use cases, database schema, and UI mockups), and implementation using Next.js for an integrated frontend-backend architecture and Prisma ORM with PostgreSQL for data management. Delivered components include a landing page, admin dashboard, user dashboard, and a Campus Space module for topic-based discussions. Findings indicate the platform improves alumni connectivity and streamlines institutional data management. Recommended next steps include developing a mobile version and further optimizing topic features for performance and usability.
Co-Authors Arief Febrian Haryono, Wasis Matheos Oktavio Selan Perani Rosyani Rifqi Surya Bernada