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I’m an undergraduate data science student passionate about machine learning and deep learning, with experience in forecasting, classification, image recognition, and image generation. I enjoy working with both structured and unstructured data, building dashboards, web applications, and interactive visualizations that make insights easy to understand. Outside of coding, I’m an energetic communicator who loves public speaking and hosting events as an MC as well hone my skills that help me engage with people and keep the energy alive in any team.
One of my key projects involved building a deep learning forecasting model using LSTM. Even though the tuned model performed better than other options, the MAE and MSE values were still relatively high compared to the target range. This taught me that accuracy isn’t just about model tuning, but also about understanding the data itself handling noise, engineering informative features, and exploring alternative architectures. It was a valuable lesson in combining technical rigor with clear communication to turn complex results into meaningful insights.
Served as the Person in Charge of event organizer division for the Data Science Club, successfully leading and coordinating three major events:
1. DSC WDB (Waktu DSC Berbuka): fostering connection and inclusivity during Ramadan.
2. Smash N Fest: encouraged teamwork, sportsmanship, and bonding.
3. DSC Kind: led a social outreach program at an orphanage.
Strengthened my event planning, leadership, teamwork, and communication skills.
Developed and deployed a machine learning model to predict the probability of hotel booking cancellations. The solution was built using FastAPI for the backend API and integrated with a Streamlit web app for user interaction. Users can input booking details such as lead time, guest type, room type, price, and special requests to receive real-time predictions along with probability scores and feature contribution analysis (SHAP values).
Strengthened my skills in end to end ML pipelines, model deployment, and building interactive data applications.
Designed and trained a deep learning model to detect ships from aerial imagery, leveraging the YOLOv8 architecture for real-time object detection. The workflow combined exploratory data analysis of bounding boxes, preprocessing and augmentation of images to 1024×1024 resolution, and dataset conversion for YOLO training. Through iterative experiments and parameter tuning, the model steadily improved across epochs, reaching 0.75 precision and 0.52 mAP50.
Sharpened my expertise in deep learning pipelines, computer vision, and model optimization.
In this project, I developed machine learning models to classify seven nutritional status categories using lifestyle and demographic data from Kaggle. The process included data cleaning (median imputation for missing values, duplicate removal, outlier detection), feature preparation across 17 variables, and the implementation of both Neural Network and Random Forest classifiers. The Neural Network achieved an accuracy and F1-score of 0.89, while the Random Forest slightly outperformed as a baseline.
Improved skills in data cleaning, feature preparation, neural networks, and predictive modeling.
Conducted a comprehensive data analysis project on the Quality of Education in Indonesia (2022) using datasets from BPS and Kemendikbud Ristek. The workflow included data cleaning (handling missing values, duplicates, and outliers), data transformation, and developing an interactive Shiny dashboard with multiple visualizations. Key findings revealed significant disparities in teacher and library distribution across provinces (with West Java leading and North Kalimantan lagging), a steady increase in school participation rates from 2002 to 2022, and a strong negative correlation between poverty and educational attainment (p < 0.001).
Sharpened my skills in R programming, statistical analysis, and data visualization.
Served as the event moderator for DSC Cascade, bringing an energetic and fiery spirit to the stage while engaging both speakers and participants. I facilitated discussions with clarity and confidence, while leveraging strong improvisational skills to adapt quickly to unexpected situations.
Sharpened my public speaking, audience engagement, and adaptability.
As Vice Secretary, I was responsible for coordinating organizational administration, managing documentation, and ensuring smooth communication between divisions. I collaborated with cross-department teams to plan and execute school-wide events, while maintaining structured records and reports for accountability.
Honed my leadership, time management, organizational skills, and effective communication.