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Data Analyst with 1+ years in data analytics and business strategy
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Management graduate from Universitas Gunadarma with a strong foundation in risk management, strategic planning, and business analysis. Experienced in market analysis, business strategy formulation, and data-driven decision-making through academic projects and certifications in data analytics and investment analysis. Passionate about transitioning into the data science field, focusing on leveraging analytical skills and problem-solving abilities to generate impactful business insights through data.
University of Gunadarma
Management
August 1, 2019 – September 1, 2023
Pikiran Rakyat
Data Analyst | Pikiran Rakyat (Internship)
September 1, 2025 – November 1, 2025
India
PT Prima Graha Bangun Tunggal
Admin | PT Prima Graha Bangun Tunggal (Internship)
April 1, 2024 – December 1, 2024
India
CV Kayu Sejahtera
Admin | CV Kayu Sejahtera (Internship)
January 1, 2024 – March 1, 2024
India
Hotel Booking Analysis
September 1, 2025 – June 1, 2026
Analyzed price behavior (ADR) and cancellation patterns to optimize hotel revenue. Key Insights: ADR increased from 2017–2019; family travelers had the highest ADR. Peak season (July-August) generated the most revenue; low season (Nov-Dec) required promotional planning. Average cancellation rate exceeded 30%, highest in January (57%) and December (49%). Repeated and loyal guests showed more stable booking behavior. Segment Insights: Long-stay guests suited for extended-stay packages; family segment most profitable; loyal customers most consistent and least likely to cancel.
Machine Learning for Hotel Booking Cancellation Analysis
September 1, 2025 – June 1, 2026
Built predictive models for hotel cancellations using Random Forest, XGBoost, Logistic Regression, and Decision Tree; Random Forest achieved the best performance with Accuracy = 0.88, Recall = 0.79, and ROC-AUC = 0.95. Cross-validation confirmed model stability and generalizability; hyperparameter tuning provided no major improvements over the baseline. Identified key drivers: Deposit Type, Lead Time, Country, ADR, Market Segment, and Special Requests. Operational Insight: The model accurately detected 79% of cancellations (Precision = 0.87), showing that cancellations were more influenced by booking policy than by guest demographics.
Food Delivery
August 1, 2025 – June 1, 2026
Analyzed factors affecting delivery time and found distance as the dominant factor (correlation = 0.78). Revealed that bad weather and traffic congestion increase delivery delays, while vehicle type impacts delivery efficiency.
Zomato Delivery
August 1, 2025 – June 1, 2026
Developed an XGBoost model to predict delivery delays and performed hyperparameter tuning that improved model stability, reducing overfitting by 44 percent and slightly improving test accuracy metrics MAE by 2 percent and RMSE by 2 percent. Identified key factors driving delays including traffic density weather multiple deliveries courier rating courier age and delivery distance. SHAP analysis revealed clear patterns where traffic and bad weather slowed deliveries while clear weather and higher rated couriers improved performance.
E-Commerce Business Transaction
July 1, 2025 – June 1, 2026
Performed customer segmentation using K-Means and RFM analysis, identifying three main segments: Occasional, At-Risk, and Loyal Customers. Insight: The majority of customers showed potential for improvement through promotion and retention strategies, while loyal customers should be maintained for long-term business value.
Electronic Sales - Customer Segmentation
May 1, 2025 – June 1, 2026
Analyzed customer data and sales performance to identify market segments. Assessed product contributions to overall sales and revenue, comparing loyalty and non-loyalty customer behavior. Insight: Smartphones ranked highest in sales and revenue as a core product, while headphone sales acted as a rebound driver to recover performance. Found that loyalty members contributed less to total sales and revenue compared to non-members, leading to recommendations for more effective marketing strategies.
English Certificate
EF SET
September 1, 2025 – Present
Data Science Bootcamp
DIBIMBING
September 1, 2025 – Present
Global Youth Preneur
IYIS
February 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects show a diverse range of applications for data analysis, from e-commerce and food delivery to hotel booking and electronic sales, indicating adaptability and a broad interest in different business domains. Participation in the International Youth Innovation Summit and collaboration in cross-cultural teams suggest a proactive and team-oriented mindset. The focus on generating impactful business insights aligns well with a data-driven culture. However, the experience is primarily academic and internship-based, which might require some adjustment to a fast-paced corporate environment.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving, and teamwork skills through various academic projects and an internship. Their ability to present insights and collaborate with teams (e.g., editorial team at Pikiran Rakyat) indicates good communication and operational fit. The experience in administrative roles also suggests an organized and detail-oriented approach, which is beneficial for data accuracy and reporting.