Curriculum Vitae
Agrilia Gracia
My vision is to grow as a competent, innovative, and integrity-driven data scientist who transforms data into valuable insights to support strategic decision-making. Guided by the principle of to serve, not to be served, I aim to contribute meaningfully and create a positive impact for organizations and society. I am particularly interested in data science and machine learning, big data analytics, and data-driven decision making, with a strong passion for research and innovation. I also aspire to apply data science across diverse fields including business, healthcare, energy, and the environment, while continuously learning and collaborating to deliver solutions that matter.
Agustus 2025
Institut Teknologi Bandung
S1 • Fisika • IPK 3.27
September 2024 - Februari 2025
Data Analyst & Collector
BPBD Jawa Barat • Magang
I worked on a research project titled “Determination of Tsunami Evacuation Routes in Pangandaran Beach Using Dijkstra, Modified Dijkstra, and Ant Colony Optimization (ACO)”. The project focused on applying graph-based algorithms and optimization methods to identify the most effective evacuation routes in a tsunami-prone coastal area. I conducted spatial data processing and analysis to model road networks, evaluated route efficiency based on distance and safety factors, and compared the performance of traditional Dijkstra, Modified Dijkstra, and ACO algorithms. The outcomes provided insights into optimizing disaster evacuation planning and supporting decision-making for local disaster management agencies.
Media
Juli 2024 - Agustus 2024
Data Analyst Intern
PT Pertamina Hulu Kalimantan Timur • Magang
I worked on a data analysis project in Bunyu Field, North Kalimantan, using an oil and gas production dataset consisting of 2,278 rows and 30 variables. The project involved performing data segmentation through multi-class classification to identify productive areas, analyzing correlations between production variables and rock characteristics, and creating spatial visualizations of potential oil and gas zones. In addition, I developed and evaluated machine learning models to predict labels on new data while addressing data limitations, such as the absence of geological maps and reserve information, through a data-driven analytical approach.
Media
Februari 2025
Machine Learning for Precision Agriculture
GEOSOFTWARE.ID • A.C.0309/RC-ML/I/2025
I completed the Machine Learning for Precision Agriculture training by Geosoftware.ID (January–February 2025, 16 learning hours), where I gained practical skills in Python for geospatial data, Sentinel-2 satellite imagery processing, and data preparation using QGIS. The program covered feature engineering, dataset creation, and the development of machine learning models using Ensemble Decision Trees and Artificial Neural Networks (ANN). I also learned hyperparameter tuning and model evaluation, both quantitatively and visually, and applied these methods in a mini project focused on optimizing precision agriculture mapping.
Media
Juli 2024
Sertifikasi BNSP Data Science
LSP P3 Teknologi Digital • 63111 2511 5 0099392 2024
Sertifikasi BNSP Data Science
Media
Mei 2024
Data Science
Digital Skola • 024/BC/GRD/XXX35/V/2024
During the Digital Skola Data Science Bootcamp, I gained comprehensive skills ranging from data processing and statistical analysis to the application of machine learning. The curriculum covered Python programming, data exploration and cleaning, data transformation, visualization, and dashboard creation to support decision-making. I completed hands-on projects such as production data analysis, interactive visualization, and the development of machine learning models for classification and prediction tasks. The bootcamp also strengthened my ability in data storytelling and professional reporting aligned with industry practices. As preparation for the BNSP (National Professional Certification Agency) examination, I was trained to build a portfolio, understand the national competency standards (SKKNI) in data science, and present analysis and models in a professional manner.
Media
Oktober 2023
Data Analysis
MySkill • MS-27/10/2023-OKE6RiZv3fzYcj45sQiQ
I completed the MySkill Data Analysis Bootcamp, where I built a solid foundation in data analytics through both theory and hands-on practice. The program introduced me to the fundamentals of data analysis and basic statistics, followed by techniques in data formatting and data cleansing to ensure data accuracy and reliability. I also developed practical skills in SQL for querying databases and Python for data manipulation and analysis. Additionally, I gained experience in creating insightful data visualizations to communicate findings effectively and support data-driven decision-making.
Media
Juli 2023
Python Basic
Digital Skola • 608/MB/PYB/CPN/VII/2023
During the Digital Skola Mini Bootcamp – Python Basic, I learned and practiced fundamental programming concepts using Python. The program covered essential topics such as data types, variables, conditional statements, loops, and functions. I also explored basic data structures including lists, tuples, dictionaries, and sets, as well as file handling for data input and output. Through hands-on exercises and mini projects, I applied these concepts to solve problems, automate simple tasks, and perform basic data manipulation, which built a strong foundation for further learning in data analysis and data science.
Media
Juni 2023
Crash Course on Python
Coursera • 8EH2XWMJTRER
The course provided foundational knowledge of Python programming including basic structures such as strings, lists, and dictionaries; writing short Python scripts for automation; understanding computational thinking, algorithms, debugging, and programming principles; and using an integrated development environment. You also gained skills in data structures, problem-solving, and an understanding of when and how to use Python for automating tasks.