Farras Azhary Rahmadi
Full Stack Software Engineer & Data Analyst crafting modern, scalable, and data-driven web applications.
About Me
I am a passionate Software Engineer with a strong foundation in both Frontend and Backend development. I love building tools that solve real-world problems and analyzing data to drive decision making.
With experience in **React**, **Node.js**, **Python**, and **Database Management**, I enjoy taking ideas from concept to deployment. I strive for clean code, responsive design, and optimal performance in every project I undertake.
Experience
Full Stack Developer
Freelance / Personal Projects
Developed various web applications including an Enterprise Resource Planning (ERP) system with Next.js, FastAPI, and Docker. Focused on performance and modular architecture.
Data Analyst
Growth Analytics Corp
Analyzed business metrics and built interactive dashboards using Python, SQL, and PowerBI. Improved reporting efficiency by 40%.
Software Engineering Intern
Tech Startups
Assisted in building frontend components using React and styled-components. Gained experience in agile methodologies.
Projects
Enterprise Resource Planning (ERP)
Ongoing
A comprehensive ERP dashboard for managing sales, logistics, and stock monitoring. Built with Next.js (MUI), Prisma, and Docker.
ADAM (Automated Data Analysis and Media)
Jul 2025 - Agu 2025
An AI-powered automation system that integrates with WhatsApp to analyze, generate, and manage data/media. Implemented RAG (Retrieval-Augmented Generation) for knowledge retrieval, enabling the system to check database contents and prevent duplication during document analysis. The project covers document OCR, image and video analysis, audio transcription, automated data entry into Google Sheets, and AI-generated text, image, video, and audio responses.
Analysis of Procurement Process Efficiency and Supply Quality
Jun 2025 - Jun 2025
Developed an automated data pipeline and validation system to monitor procurement KPIs, enabling real-time insights into supplier performance, delivery timeliness, and compliance, which supports strategic sourcing decisions and operational efficiency.
Visual Forensics: Deep Learning for Insurance Fraud Detection
Jun 2025 - Jun 2025
Developed a deep learning-based image classification model to detect fraudulent vehicle damage claims, enabling insurers to automate fraud screening and reduce financial losses through more accurate and scalable claim validation.
Optimizing Auto Insurance Risk: A Machine Learning Approach to Claim Prediction
Mei 2025 - Mei 2025
Developed a machine learning model to predict whether a customer will file an auto insurance claim, supporting insurers in optimizing premium pricing, managing risk exposure, and enhancing profitability through more informed underwriting decisions.
Bank Marketing Analysis
Apr 2025 - Apr 2025
This project aims to enhance the effectiveness of deposit marketing campaigns in the banking industry by identifying key factors that influence customer’s decisions to subscribe.