Juli 2024

Universitas Brawijaya

S1 • Teknik Komputer • IPK 3.48

Oktober 2024 - Juli 2025

PT Aero Systems Indonesia • Magang

At PT Aero System Indonesia (Garuda Indonesia Group), I was actively involved in multiple data-driven and strategic IT projects that aligned closely with business objectives. In the Cybersecurity Division, I supported the Security Operations Center (SOC) for PT Citilink Indonesia and participated in the Endpoint Protection Project, utilizing FORTISEM, CrowdStrike, and plunk for log analysis, threat detection, and compliance—contributing to secure big data environments. I developed detailed business processes for strategic initiatives like the Corporate Business Trip Platform and E-Commerce Platform by applying tools such as Microsoft Visio, Lucidchart, and JIRA, showcasing strong attention to detail, analytical thinking, and collaborative problem-solving. For data management and executive reporting, I designed a Corporate Performance Dashboard at ACS, transforming raw operational data into visual insights using Power BI, Excel (Advanced Functions), and Tableau—enhancing decision-making across departments. I also led the technical documentation and system alignment of Odoo ERP integration at PT GDPS, using UML, ERP tools, and Confluence to ensure seamless implementation. My role required consistent use of Microsoft Office, structured data processing, and communication of insights to stakeholders—skills essential for data-driven roles including dashboard channel optimization and event coordination.

Januari 2023 - Januari 2025

Mugen Group • Part Time

Management Sales and Strategy: Executed sales strategies for game accounts on international marketplaces, achieving a turnover of 1.2 billion IDR in 2023 and winning "Best Performance" in April 2023 with 150 million IDR in sales. Management Relationship Customer: Closed over 1,000 transactions with an 85% success rate and built partnerships with 35 account resellers. Data Analysis and Market Insights: Developed a dashboard for tracking sales trends and optimized profit marginsthrough data scraping with tool python and k-near neighbors algorithm, achieving a 98% positive reputation score.

Juni 2025

Guide to Learn Python

DQLAB • #DQLABAI001IRKRDA

Completed the Guide to Learn Python with AI course at DQLab, an applied learning program designed to introduce the fundamentals of Python programming in the context of Artificial Intelligence (AI) and automation. Through this course, I strengthened my understanding of Python syntax, control structures, functions, and data types, while also exploring their application in basic AI tasks. The training emphasized real-case implementations, including logic building for decision-making, rule-based automation, and data preprocessing using pandas, NumPy, and Python's native capabilities. I practiced constructing scripts that simulate intelligent behavior, laying the groundwork for future development in AI and machine learning workflows. The course also covered how Python can be integrated with analytical tools and datasets to generate early-stage automation and predictive logic. This program enhanced my algorithmic thinking, precision in coding, and readiness to approach more advanced topics in AI and Data Science using Python as a primary tool.

Media

Juni 2025

Python Fundamental for Data Science

DQLAB • #DQLABINTP1IMBLVU

Completed the Python Fundamental for Data Science course at DQLab, a practical and beginner-friendly program designed to build a strong foundation in Python programming for analytical purposes. During this training, I developed core competencies in data manipulation, data cleaning, and basic statistical analysis using essential Python libraries such as pandas, NumPy, and matplotlib. I learned to write clean and efficient code to load, process, and transform structured datasets from various formats including CSV and Excel. The course emphasized real-world data case studies, such as sales performance analysis and customer behavior insights, which allowed me to build logical problem-solving skills and apply Python functions for EDA (Exploratory Data Analysis). I also gained exposure to building simple visualizations and understanding data patterns to support business understanding. This experience enhanced my ability to work with data programmatically, preparing me for more advanced topics in data science and analytics, and giving me a solid technical base to support data-driven decision making.

Media

Mei 2025

Belajar Dasar Visualisasi Data

Dicoding • ERZRE3YDQXYV

Completed a foundational training program in Data Visualization that focused on translating raw data into meaningful visual narratives to support strategic business decisions. During the training, I developed practical skills in creating insightful dashboards, trend charts, and interactive reports using industry-standard tools such as Power BI, Looker Studio, Microsoft Excel (Advanced Charts & PivotTables), and Tableau. I learned how to apply best practices in data storytelling, visual hierarchy, and layout optimization to present KPIs clearly and effectively to diverse stakeholders. The training emphasized real-world scenarios including sales performance tracking, customer segmentation analysis, and operational reporting. I also gained hands-on experience in connecting multiple data sources (CSV, Excel, SQL), cleaning and transforming data, and building dynamic visualizations that respond to user inputs through filters and slicers. This training sharpened my analytical thinking, attention to detail, and ability to turn complex datasets into accessible visual insights that enhance decision-making and organizational clarity.

Media

Januari 2025

Data Sciece & Analytics

HP Foundation • 514f2431-ac53-4e4f-9f01-aa6df9ebc1ce

Completed an intensive Data Science & Analytics training program designed to build strong foundations in statistical analysis, data processing, and predictive modeling. Throughout the program, I gained hands-on experience using Python (pandas, NumPy, scikit-learn, matplotlib, seaborn) and SQL to clean, manipulate, and analyze large datasets from real-world scenarios. I developed the ability to formulate analytical questions, identify key metrics, and apply data-driven approaches to solve business problems. The curriculum covered essential concepts in exploratory data analysis (EDA), hypothesis testing, correlation analysis, and feature engineering. I also applied supervised and unsupervised machine learning algorithms (e.g., regression, classification, clustering) to build models that support smarter decision-making. Additionally, I learned to communicate insights clearly using visual reports and dashboards through Power BI and Looker Studio, effectively bridging technical analysis with business context. This program strengthened my analytical thinking, problem-solving ability, and readiness to contribute to data-centric environments.

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