I'm an Informatics student at Institut Teknologi Bandung with a strong passion for software engineering, data science, and machine learning. Currently engaging in data science and research.
My experience spans full-stack development, AI engineering, and data science, with hands-on work at companies like Fata Organa and various project-based roles. I've built scalable applications using modern technologies and developed machine learning models for real-world applications.
I'm actively involved in competitive programming and data science competitions, which continuously sharpen my problem-solving skills and analytical thinking. Through these challenges, I apply concepts in optimization, statistical modeling, and algorithm development.
BS in Computer Science
Relevant Coursework: Data Structures & Algorithms, Software Engineering, Machine Learning, Computer Architecture, Geometry and Linear Algebra, Discrete Mathematics
Developed an agentic AI for Question-Answering system within a Project Management System, enhancing information retrieval and user interaction. Implemented automated developer assignment system using intelligent task matching algorithms.
Built machine learning model for ONNX runtime predicting corrosion rates for 9 materials in sulfidic/naphthenic acid conditions. Achieved exceptional RMSE of 0.3 and completed project 1 month ahead of schedule.
Designed robust database architecture for company's SOP using ERD and Sequelize ORM with PostgreSQL. Developed RESTful APIs and implemented comprehensive testing with Jest and Supertest.
Annotated 100+ frames per day for computer vision models, working with 10 object categories including person, vehicle, and safety-related objects. Maintained high-quality labeled datasets using XML annotation format.
Developed and structured data science and machine learning challenges for Datavidia, ensuring a diverse range of problem difficulties and real-world applications. Also conducted extensive data collection and feasibility testing on problems.
Ensured high-quality and relevant datasets for competition tasks and validated problem fairness.
Designed and formulated high-quality algorithmic and mathematical problems for the competition. Created problem sets across multiple domains and developed Higher-Order Thinking Skills (HOTS) problems to test participants' deep problem-solving skills.
Ensured a smooth and challenging experience for participants by providing fair and correct problems.
A continuously flowing showcase of my expertise in machine learning, web development, and data science.
Interactive Tableau dashboard analyzing the impact of social media on education in Indonesia. Built custom web scraping pipeline and reached final round of COMPFEST 16 among nationwide participants.
Full-stack sign language learning platform with real-time hand gesture recognition. Built using computer vision and machine learning for preprocessing and model training with React frontend.
Machine learning model for ONNX runtime that predicts corrosion rates for 9 materials in sulfidic/naphthenic acid conditions. Achieved exceptional RMSE of 0.3 with high predictive accuracy.
Web-based inventory and donation management system supporting 50+ local SMEs in Jatinangor. Built with robust backend services using REST APIs and Firebase integration.
Forecasting model using Singular Spectrum Analysis on daily food commodity prices in Bandung, Indonesia. Demonstrated SSA's ability to identify trends and seasonal patterns.
Interactive Tableau dashboard analyzing the impact of social media on education in Indonesia. Built custom web scraping pipeline and reached final round of COMPFEST 16 among nationwide participants.
Full-stack sign language learning platform with real-time hand gesture recognition. Built using computer vision and machine learning for preprocessing and model training with React frontend.
Machine learning model for ONNX runtime that predicts corrosion rates for 9 materials in sulfidic/naphthenic acid conditions. Achieved exceptional RMSE of 0.3 with high predictive accuracy.
Web-based inventory and donation management system supporting 50+ local SMEs in Jatinangor. Built with robust backend services using REST APIs and Firebase integration.
Forecasting model using Singular Spectrum Analysis on daily food commodity prices in Bandung, Indonesia. Demonstrated SSA's ability to identify trends and seasonal patterns.
Interactive Tableau dashboard analyzing the impact of social media on education in Indonesia. Built custom web scraping pipeline and reached final round of COMPFEST 16 among nationwide participants.
Full-stack sign language learning platform with real-time hand gesture recognition. Built using computer vision and machine learning for preprocessing and model training with React frontend.
Machine learning model for ONNX runtime that predicts corrosion rates for 9 materials in sulfidic/naphthenic acid conditions. Achieved exceptional RMSE of 0.3 with high predictive accuracy.
Web-based inventory and donation management system supporting 50+ local SMEs in Jatinangor. Built with robust backend services using REST APIs and Firebase integration.
Forecasting model using Singular Spectrum Analysis on daily food commodity prices in Bandung, Indonesia. Demonstrated SSA's ability to identify trends and seasonal patterns.
Interactive Tableau dashboard analyzing the impact of social media on education in Indonesia. Built custom web scraping pipeline and reached final round of COMPFEST 16 among nationwide participants.
Full-stack sign language learning platform with real-time hand gesture recognition. Built using computer vision and machine learning for preprocessing and model training with React frontend.
Machine learning model for ONNX runtime that predicts corrosion rates for 9 materials in sulfidic/naphthenic acid conditions. Achieved exceptional RMSE of 0.3 with high predictive accuracy.
Web-based inventory and donation management system supporting 50+ local SMEs in Jatinangor. Built with robust backend services using REST APIs and Firebase integration.
Forecasting model using Singular Spectrum Analysis on daily food commodity prices in Bandung, Indonesia. Demonstrated SSA's ability to identify trends and seasonal patterns.
Sharing knowledge through technical articles and academic research. From algorithms to AI, exploring the world of computer science.
Reflection on how major university assignments can provide new perspectives in the rapidly evolving AI era.
DFS and BFS algorithms are fundamental algorithms, meaning all programmers should at least know about these two algorithms.
Decision Tree is one of the Machine Learning algorithms widely used for prediction. This article discusses the basic concepts of Decision Trees.
Experience and reflection during the first semester studying Informatics Engineering at Institut Teknologi Bandung.
Explored four different text preprocessing strategies for sentiment analysis of Indonesian text, comparing them with a Gensim baseline. Contributed comprehensive evaluation framework using TF-IDF and SVM classification.
Proposed custom decision tree model to handle missing values during data splitting for nonlinear multivariate imputation tasks. Achieved notable average RMSE of 4.98 on synthetic educational dataset.
Developed forecasting model using SSA on daily food commodity prices in Bandung, Indonesia. Demonstrated SSA's ability to identify trends, seasonal patterns, and noise in non-stationary time series.
I'm always interested in new opportunities in software engineering, data science, and machine learning. Whether it's an internship, research collaboration, or project work, I'd love to connect.
rizkyfathur326@gmail.com
@fathurwithyou
@fathurwithyou
@fathurwithyou
@fathurwy