LearnNet – Media Pembelajaran Digital Interaktif LearnNet adalah produk digital learning media interaktif yang dikembangkan oleh mahasiswa Program Studi Pendidikan Teknologi Informasi, Universitas Brawijaya. Proyek
Design
Creative Projects
innovation created by students during capstone project, courses or Field Practice to boost their experience
Have You Hit Up Our YouTube Channel? Learn More ViBeLearn adalah instructional content initiative yang bertujuan untuk mendukung pembelajaran inklusif bagi siswa sekolah menengah. Proyek
Introducing bangunIN👀 A YOLOv8-Based Drowsiness Detection System Integrated with Cloud Computing and a Fault-Tolerant System 📝Project Domain: Project Short Description This project focuses on
SmartEDU Satu Platform, Semua Solusi Pembelajaran Digital Sekolah Anda! Platform Learning Management System (LMS) berbasis web yang dikembangkan untuk mendukung proses pembelajaran digital. Contact us
Learning Management System (LMS) KinoLearning KinoLearning adalah sistem manajemen pembelajaran (LMS) untuk mata pelajaran Informatika di SMAN 1 Kalidawir. Dilengkapi dengan fitur chatbot AI, akses
Capstone Project InnoLearn Developing a comprehensive inclusive education framework that ensures accessibility, equity, and meaningful participation for all learners in diverse learning environments. Membangun Pembelajaran,
RIVER SENSE River Water Quality Detection System Based on AIoT 📖 Project Overview This project develops a real-time River Water Quality Monitoring System based
SiPintar SIPINTAR atau Situs Pembelajaran Informatika Terpadu dan Interaktif adalah media pembelajaran digital berbasis Google Sites yang menyajikan infografis, slide interaktif, dan video pembelajaran untuk
Smart Lele | AIoT for Automated Catfish Pond Management 🐟💻 Introducing Smart Lele, an innovative AIoT (Artificial Intelligence of Things) project designed to revolutionize catfish
Vision-based Smart Parking System Vision-Based Smart Parking System is a prototype using ESP32-CAM and Edge AI provides real-time slot availability and congestion prediction through image processing,