Hello there! I'm

Muhammad Henry Aditya

Fullstack Web Developer | Machine Learning Engineer

About Me

I have a strong passion for full-stack web development and machine learning, with a keen interest in exploring the rapidly evolving potential of AI. As technology continues to advance, I am committed to continuously expanding my knowledge and honing my skills to stay at the forefront of innovation. By leveraging my expertise in software engineering, I aim to contribute to the development of cutting-edge solutions that drive efficiency, automation, and intelligent decision-making in various industries.

My Journey

A timeline of my academic and professional experiences.

Education

Undergraduate

Lambung Mangkurat University - Computer Science

August 2022 - February 2026

Experience

InternshipOn-site

QA Engineer, Junior Full Stack Developer at Ruang Algo Multimatics

February 2024 - June 2024

Banjar Baru, South Kalimantan, Indonesia

InternshipOn-site

Junior Machine Learning Engineer, Fullstack Web Developer at UPA TIK, Lambung Mangkurat University

September 2025 - October 2025

Banjar Baru, South Kalimantan, Indonesia

InternshipHybrid

Digital Marketer, Web Developer at CV. Iqromaya Global Mandiri

October 2023 - Desember 2023

Collaborate professionally with MSMEs and the South Kalimantan Provincial Government in the preparation of MSME catalogs by digitising with website.

InternshipRemote

React.js Front-end of Independent Study Program at PT. Hacktivate Teknologi Indonesia

September 2024 - Desember 2024

Developing E-Commerce Front-end Web Applications based on React.js

My Expertise

A showcase of my projects, skills, and qualifications.

Featured Projects

React.jsTailwind CSS

MHStore - Buy What You're Looking For

November 2024 - Desember 2024

I have finished my capstone project related with my MSIB Programme in PT. Hactivate Teknologi Indonesia, MHStore. MHStore is a modern e-commerce web application built with ReactJS + Vite and styled using Tailwind CSS with Flowbite-React components.

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Vue 3TypeScript

EditCitra - Real-Time Image Processing Tool

September 2024 - October 2024

A browser-based image processing application built with Vue 3 to provide an accessible and interactive experience. The creators who built this application are Muhammad Henry Aditya, Maulana Ansari. As co-developer, I focused on implementing a range of image manipulation algorithms and building a user-friendly interface that features a live preview for immediate feedback. Implemented Operations: Thresholding, Negative Image, Brightness/Contrast Adjustment, Grayscale Conversion, Rotation, Flipping, Histogram Equalization, and Convolution. Core Technologies: Vue 3 and TypeScript.

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Next.jsReact.js

HandwrittenOCR Frontend – AI-Powered OCR Frontend

June 2025 - June 2025

HandwrittenOCR Frontend is a modern web application built with Next.js, designed to interact with an intelligent OCR backend system. It allows users to upload or scan images containing handwritten or mixed-format text and receive accurate text recognition results via a connected backend.

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Laravel 12 (API)Flask Python APIMySQLJWT

HandwrittenOCR – Intelligent OCR Backend System

June 2025 - June 2025

HandwrittenOCR is a full-stack backend system that combines Laravel (v12) and Flask to enable intelligent recognition of handwritten and mixed-format text (e.g., “ADjh90K7”). It supports user and admin management, image uploads, and integration with a PyTorch-based OCR engine powered by EasyOCR.

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PythonFlaskComputer VisionDeep LearningMachine LearningYOLO v11HTMLCSS

Real-Time AI Object Detection Web Application

June 2025 - July 2025

Developed a full-stack web application to perform real-time object detection on a live video stream. The application leverages a Python backend to run a YOLO (You Only Look Once) version 11 as a deep learning model, processing video frames from a server's webcam and streaming the results to a dynamic web interface. The interface, built with HTML, CSS, and JavaScript, displays the live video feed and detection results, including class names and confidence scores and implements API endpoints to facilitate seamless communication between the frontend and the backend computer vision logic.

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