I focus on building data-driven solutions and exploring deep learning for real-world applications. Throughout my journey, I’ve worked with Python, Data Science, and Artificial Intelligence — developing projects that connect theory with practical use. From data preprocessing and model optimization to explainable AI, I aim to transform data into meaningful insights that support better decision-making. Currently seeking opportunities as an AI Engineer, Data Analyst, or Data Scientist.
In collaboration with dr. Tengku Winda Ardini, M.Ked (Cardio), SpJP (K)
ARDINI is a deep learning–based system for automated analysis of echocardiography videos, designed to detect valvular heart disease with improved efficiency and accuracy. The system bridges AI and medical diagnostics to support faster and more reliable clinical decisions.
Optimized inference of YOLOv11 for real-time vehicle detection and counting, achieving up to 3× faster performance on CPU and GPU compared to baseline models.
Understand customer behavior over time through cohort-based retention analysis segmented by join month, quarter, and initial purchase activity. Use these insights to improve customer loyalty and long-term value.
Understand your customers better through RFM analysis to segment, target, and retain high-value users effectively.
Boost product sales by uncovering hidden purchase patterns and recommending items based on customer buying behavior using Market Basket Analysis.
PredictaCycle transforms Windows battery reports into actionable insights, helping users understand usage trends, capacity decline, and predict future performance with data analysis and machine learning.
Bring black-and-white images to life by automatically generating realistic colors using a deep learning model based on the U-Net autoencoder architecture.
ResBuddy is an AI research assistant that extracts key insights from academic papers using RAG, DeepSeek-R1:1.5B, nomic-embed-text, ChromaDB and Streamlit, providing context-aware responses in an intuitive interface.
Boost Superstore sales with data-driven insights! This dashboard analyzes USA supermarket sales (2021-2022) through Overview (key metrics & trends), Product (profitability & efficiency), and Customer (segmentation & buying patterns).
Curious about your child's height at age 5? Try DEDEL, a machine learning-based prediction tool. It also offers resources on complementary feeding (MPASI) to raise awareness about stunting.
Maximize your company's profits by identifying potential churn early and taking action to retain valuable customers. Created by Arunika's Team
Are you curious about analyzing key data and buyer trends in a market? This Market Transaction Report offering a comprehensive view of the market's performance.
Confused about selecting fresh fish? Fishio can help! Simply take a photo of the fish's eye, and Fishio will determine its freshness. Created by Depresso Squad
Explore how we meet national food needs through an interactive map showcasing rice imports and production.
Explore the heart disease dashboard, which offers detailed insights into heart disease. The dashboard presents key data and trends, helping you analyze risk factors and patterns for better understanding and prevention.
Published in: Repositori Institusi Universitas Sumatera Utara - 2025.
Published in: 2024 8th International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM).
Published in: Jurnal Pengabdian Masyarakat Gizi Pontianak.
Heart Disease Risk Prediction: A Crucial Step for Future Prevention.
