AI learning and Software Engineer who enjoys building efficient, scalable solutions, writing clean code, designing great interfaces, and tackling challenges with creativity and a little bit of fun along the way.
As part of the Promotion Team, I actively represent the campus, coordinate promotional events, and engage with prospective students to share the BINUS experience and academic excellence.
I collaborated with a dedicated team to manage event logistics, oversee race stations, and ensure a seamless, safe, and high energy experience for all athletes. This role honed my teamwork, problem solving skills, and ability to perform in a fast-paced operational environment.
Contributing to the Google Developer Groups on Campus (GDGoC) by organizing tech events, expanding network connections, and empowering students to learn and build with Google technologies.
Planning and executing workshops, seminars, and collaborative learning sessions to support the academic growth and technical proficiency of IT students within the HIMTI community.
An interactive machine learning application and predictive system built to forecast Formula 1 pit stops based on lap level race telemetry and tyre performance data. Utilizing classical machine learning models with XGBoost, the system evaluates complex variables like tyre degradation, lap time deltas, and stint history to predict whether a driver will pit on the next lap.
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A Point-of-Sale system for small culinary businesses, built to be a free, lightweight alternative to expensive POS subscriptions. As Back-End Developer, I built the REST API with Node.js, Express, and the built-in node:sqlite module, handling JWT auth for three roles, QRIS payment via Xendit, real-time order updates, and atomic stock transactions across 15+ endpoint groups.
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A news classifier that sorts articles into four categories, built entirely with classical NLP, no pre-trained transformers. I trained and compared four models (Logistic Regression, Naive Bayes, MLP, XGBoost) on the AG News dataset using TF-IDF, then deployed it as a public Streamlit app with single-article and batch prediction.
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A lightweight parking occupancy detector that tells drivers which spots are free using classical computer vision instead of deep learning, so it runs on a normal CPU with no GPU. As Data Engineer (6-person team), I worked on the 5 step OpenCV preprocessing pipeline and the pixel-counting classifier with temporal smoothing, served live through a Flask web app.
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An early detection application for heart attacks designed to interpret smartwatch biometrics (like Heart Rate and Heart Rate Variability) into actionable, real-time alerts. Heartify aims to solve this by providing simple visual indicators and automated emergency alerts when abnormal patterns are detected.
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A UI/UX design project for a smart drug vending machine called Medigo. The design focuses on a clean, accessible interface that makes purchasing over-the-counter medicine fast and intuitive built entirely in Figma with interactive prototyping.
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A mobile app UI/UX design for a premium car rental service called Luxury Ride. The design emphasizes elegance and smooth user flow from browsing available vehicles to booking confirmation all prototyped interactively in Figma.
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A text-based alien game built in C for the Algorithm & Programming Lab. The project demonstrates core programming concepts memory management, game loops, collision logic, and structured code design all implemented from scratch in pure C.
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