Passionate about leveraging data and technology to solve real-world problems and create innovative solutions.
I am an Informatics student currently in my 6th semester with a strong interest in Data Analysis and Business Intelligence. I am passionate about transforming raw data into meaningful insights that can support decision-making and solve real-world problems.
I have hands-on experience using tools such as Power BI, Excel, Python, and SQL to analyze data, build interactive dashboards, and extract valuable insights through academic projects. My primary focus is on data analysis, where I continuously improve my ability to understand data patterns and deliver data-driven solutions.
In addition, I have foundational knowledge and familiarity with various technologies, including web development and machine learning, which I have explored during my studies. This allows me to adapt quickly to new tools and technologies when needed.
I am known for being adaptable, consistent, and solution-oriented. When learning something new, I am able to focus deeply and continuously improve until I understand it well. I enjoy problem-solving and making decisions based on data, especially in project-based environments.
My goal is to help organizations leverage data to make better decisions, improve efficiency, and create impactful solutions.
I embarked on my Informatics journey in August 2023, starting with foundational programming knowledge. Through dedication and consistent practice, I transformed initial challenges into strengths, developing robust problem-solving skills and technical expertise.
Established core fundamentals in computer science:
Developed logical thinking and mastered programming fundamentals through hands-on practice.
Advanced my programming capabilities through:
Gained confidence in software development and understood program architecture and design principles.
Deepened expertise in data and systems:
Mastered data management principles and system architecture fundamentals.
Explored intelligent systems and algorithms:
Learned to leverage data for building predictive models and intelligent solutions.
Advanced into specialized domains:
Applied knowledge to real-world projects in data analysis and machine learning.
Expanding expertise in cutting-edge technologies:
Currently focused on developing production-ready solutions and preparing for professional opportunities in Data Science.
I am dedicated to advancing my expertise in:
Imagine running a PS rental business with spreadsheets and WhatsApp. This system replaces all of that with one clean dashboard — customers browse and book online, payments process automatically, and owners watch revenue roll in real-time.
Four roles, four separate dashboards. Admins control everything. Cashiers handle walk-ins and payments. Customers book PS units, games, and accessories from a shared cart. Owners pull revenue reports and unit status with one click.
Think of it like a digital flea market where everyone is both a shopper and a vendor. List your old stuff with honest condition grades, chat with buyers directly, and build trust through reviews that only actual purchasers can leave.
The smart part — checkout validates stock in real-time and instantly rolls back if payment fails. No overselling, no angry customers. Every payment method works, and everyone gets notified the second something happens.
Most bakeries still take orders through WhatsApp and hope the bank transfer proof shows up. This system gives them a proper online store — customers browse, order, upload payment proof, and watch their order move through four clear stages until it arrives at their door.
The admin side shows exactly what matters — how much revenue came in today, which products fly off the shelf, and how many customers keep coming back. Everything exports to Excel when the boss needs numbers.
A motorcycle rental shop, fully digitized. Customers browse available motorcycles, pick their dates, and book — all online. Cashiers confirm payments and mark rentals complete with a single click. Admins oversee everything from one clean dashboard.
Every motorcycle has photos, dynamic pricing, and real-time availability. After each rental, customers leave reviews — so future renters can see which motorcycles are the crowd favorites.
Nearly 100,000 international flight records from airports across six continents — and the story they tell is surprising. Flight status splits almost perfectly into thirds: 33.3% on-time, 33.3% delayed, 33.4% cancelled. Passenger demographics are evenly balanced too — 50/50 gender split, ages spread uniformly from 1 to 80+, with North America leading at 32K passengers followed by Asia at 19.6K.
The dashboard surfaces what matters fast — which airports struggle with delays (Santa Maria, Santa Rosa), which ones stay reliable (San Pedro, Santa Ana), monthly traffic swings from 7.9K in February to 8.6K in May, and even which pilots carry the highest cancellation rates. Decision-makers can spot bottlenecks, compare continents, and optimize operations — all at a glance.
1,470 employees, 16% attrition rate — this dashboard breaks down why people leave and who is most at risk. Research & Development dominates the headcount at 961, but Laboratory Technicians (62), Sales Executives (57), and Research Scientists (47) lead the exit list. Managers and Research Directors earn the most at ~$15K/month, while HR sits at the bottom around $13K.
The dashboard connects the dots between income, overtime, job satisfaction, and attrition — so HR teams can spot flight risks before they walk out the door. Demographics, department breakdowns, promotion timelines, and compensation trends all surface in one view that turns employee data into retention strategy.
541,909 raw transaction rows across 8 columns — this is real, messy e-commerce data. Returns, zero-price items, missing customer IDs, bulk wholesale orders. After cleaning it all with Python, the dashboard reveals the full story: 4,373 customers, 25,900 transactions, and 909M in total revenue across multiple countries.
The insights are eye-opening. One customer (ID 136840) drives 54% of all revenue at 142M — a massive dependency risk. DOTCOM POSTAGE tops the product list at 16M. UK dominates sales, but Netherlands and EIRE punch above their weight. Monthly revenue climbs steadily from 52M in January to a December peak, showing clear seasonal momentum.
7,905 shipments tracking $44.7M in revenue across six product groups and three global regions. Each row is one shipment — product, salesperson, ship date, box count, and order status. The pipeline breaks down cleanly: 80.4% delivered, 10% placed, 9.6% cancelled.
Milk Bars lead revenue at $14.6M, followed by Eclairs at $10.3M. APAC dominates with 52.8% of all sales — UK, India, and the USA are the top three markets. The Delish team outperforms the rest, and revenue climbs steadily through the year, peaking at $4.5M in July. A fact-table structure built for a data warehouse, ready for deep operational analysis.
HealthScope Indonesia is an interactive analytics dashboard built using Microsoft Power BI to visualize and analyze health data from 12 provinces in Indonesia for the period 2010–2024. This dashboard is designed to assist in data-driven national health policymaking. The dashboard consists of four analytical pages: an overview of national health conditions, a comparison of performance across provinces, an analysis of factors influencing mortality rates and life expectancy, and a summary of insights and policy recommendations.
Machine Learning projects are currently in development and will be added soon.
Stay tuned for exciting ML projects including:
Have a project in mind or want to discuss potential opportunities? I'd love to hear from you. Let's create something amazing together!
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