@naufallzakki
Information Systems undergraduate at Airlangga University and BSI Scholarship awardee with experience in leadership, stakeholder coordination, partnerships, and operational project management. Developing a career at the intersection of technology, business, and organizational transformation, with interests in enterprise systems, technology risk, financial technology, and emerging technologies. Strong in communication, analytical thinking, cross-functional collaboration, and structured problem-solving.
// Academic & personal work
A growing collection of Information Systems coursework and practical experiments across data, machine learning, mobile, and web development.
Web & Mobile · 2026
A comprehensive web and mobile prototype for a blockchain-based carbon credit marketplace, engineered for transparent MRV (Measurement, Reporting, and Verification) workflows and the prevention of double offset claims.
Data & ML · 2026
A machine-learning project exploring credit default risk through structured data and model-driven analysis.
Data & ML · 2026
A lightweight, rule-based Academic Advising Decision Support System designed for faculty academic advisors at Universitas Airlangga, featuring automated KRS credit ceiling calculations, multi-semester cohort progress tracking, milestone checkpoint risk detection, and ad-hoc advising simulation.
Data & ML · 2026
An empirical machine-learning study leveraging Genetic Algorithms for optimal feature selection in Random Forest models to classify daily price movement trends on Bank Central Asia (BBCA.JK) equities.
Data & ML · 2026
Customer segmentation analysis using K-Means and K-Modes to identify distinct behavioral and spending profiles across numerical and categorical customer data.
Coursework, technical experiments, and smaller builds documenting the fundamentals behind my larger projects.
Data & ML · 2026
A regression project for estimating vehicle prices and evaluating prediction performance.
Data & ML · 2026
A classification exercise exploring data preparation, model training, and performance interpretation.
Fundamentals · 2026
A focused implementation of a decision-tree classification workflow.
Fundamentals · 2026
An academic exploration of techniques for preparing and learning from imbalanced datasets.
Fundamentals · 2026
A practical study of reducing, extracting, and selecting useful features for modeling.
Fundamentals · 2026
A fundamentals exercise focused on normalization techniques and their role in data preparation.