I turn complex data into clear, actionable insights that support better decision-making. With a background in Data Science, I build data-driven solutions from analysis and visualization to simple system development to solve real-world problems.
Graduates with Cum Laude Predicate, Best Graduates, and Outstanding Graduates
Hello, I’m Mochammad Fahd Ali Hillaby, a Data Science Technology graduate from Universitas Airlangga and recognized as the Best Graduate. I have a strong interest in data analytics and data-driven decision making.
I have experience working with data management, analysis, and reporting, including building more efficient data systems and ensuring data accuracy. I enjoy transforming raw data into meaningful insights that support business strategy and operational improvement.
Beyond technical skills, my experience as Head of Public Relations at IRIS strengthened my leadership, communication, and collaboration abilities. I’m comfortable working in dynamic environments and collaborating with diverse teams.
GPA Score
Data Projects
Built a web-based data management system using Python (Flask) to replace manual spreadsheet workflows. Developed a real-time interactive dashboard to track payment progress and manage over 500,000 rows of data effectively.
Managed and optimized the organization's WordPress website, speeding up the publishing process by 2x. Designed digital content that boosted overall social media engagement by 2.5x.
Guided over 50 students in applying multivariate statistical methods (such as MANOVA, Factor Analysis, and Cluster Analysis) using SPSS and R programming.
Analyzed employee engagement and survey opinion data using NLP techniques and K-Means Clustering. Built interactive dashboards in Tableau and Python to support strategic HR decisions.
A full-stack web application built to digitize CSR program reporting at PT Semen Indonesia, moving away from traditional spreadsheets.
Employee segmentation and survey sentiment analysis using NLP and clustering algorithms to improve HR strategies.
An intelligent early-detection system for systemic diseases through nail image analysis using Computer Vision.
Classification of traditional gamelan instruments using audio feature extraction (MFCC) and ML models, achieving 96% accuracy.
A systematic review and meta-analysis evaluating the use of Convolutional Neural Networks (CNN) for early Alzheimer's detection via MRI.
Developed an interactive Tableau dashboard to visualize and analyze customer review sentiments for Maybank branches.
A web-based smart cashier system designed to optimize transaction and inventory management for small-to-medium businesses.
Statistical modeling and analysis of an M/M/s queueing system to optimize staff numbers and customer wait times.
Applied Cox Proportional Hazard regression to study serum free light chain as a potential survival biomarker.
Analyzed demographic and psychosocial factors affecting student GPAs using an Ordinal Logistic Regression model.
Spatial and quantitative mapping of socio-economic inequality across various provinces in Indonesia.
Python, R, Machine Learning, Deep Learning, Time-Series (XGBoost, LSTM, ARIMA), NLP, Pandas, TensorFlow.
SQL, PHP (Laravel), Flask, Next.js, HTML/CSS, JavaScript, PostgreSQL.
Tableau, PowerBI, Git, SPSS, Microsoft Excel, Statistics, Geospatial Data.