Hi, I'm Windy Febbiayuni
Welcome to Windy's Analytics, where numbers tell stories and insights drive decisions. I present a collection of SQL, Python, and Tableau projects showcasing the power of data in unlocking valuable insights. Explore a diverse range of projects, from analyzing market trends to detecting fraudulent transactions and addressing societal issues like education disparities and waste management. Each project reflects my commitment to leveraging data into actionable intelligence. Join me on a journey of discovery, where analytics meets innovation.
Credit Card Fraud Detections
Credit card fraud, a widespread issue in payment systems, involves the unauthorized use of payment cards for illicit purposes. This project centers on fraud detection within a dataset containing credit card transactions made by European cardholders in September 2013. The project delves into pre-processing steps, encompassing data cleaning and logistic regression analysis for fraud detection. The statistical overview provides insights into the distribution of normal and fraudulent transactions, emphasizing the critical need for accurate classification due to the significant financial impact of fraud. The analysis highlights the model's performance measures using a confusion matrix, classifying the type I and type II errors, ultimately contributing to a nuanced understanding of fraud detection challenges and opportunities.
Market Reaction to Cigarette Excise Increase Announcement 2019-2022
This project tests two hypotheses and explains the market reaction based on event study methodology, focusing on three prominent companies: Gudang Garam, HM Sampoerna, and Wismilak. The dataset includes historical IHSG data and stocks of the mentioned companies. The t-test, PMF, correlation analysis, and descriptive statistics are used to explain the significance of abnormal returns in influencing investor decisions and shaping market perceptions in response to cigarette excise tax policies. The project offers insights into the market dynamics surrounding cigarette excise tax policies in Indonesia, contributing to a nuanced understanding of investor behavior and market reactions in response to regulatory changes.
Olist E-Commerce Product Analysis
Engaging with the Olist Brazilian e-commerce public dataset, encompassing 100k orders spanning 2016 to 2018, this project delves into intricate product analysis. The specific objectives include uncovering insights into products with the highest and lowest sales, tracking the highest product sales growth throughout 2016–2018, identifying Olist's peak traffic hours, and pinpointing cities with the highest order volumes. Explore the comprehensive analysis that unveils patterns and trends within the Olist Store's dynamic marketplace.
People Analytics
In this project analysis, a comprehensive examination of workforce dynamics unfolds, revealing intricate patterns and correlations within the data. The exploration encompasses diverse aspects, including target achievements, city-wise performance, overwork cultures, and the nuanced interplay of working days with take-home pay. Notably, the data elucidates disparities in employee practices, such as working on holidays and engaging in overtime, influencing acquisition outcomes. This insightful investigation provides a data-driven lens into the complexities of staffing operations, offering valuable insights for strategic decision-making and tailored interventions to optimize workforce performance.
Waste Problem in Indonesia
This project delves into the critical issue of Indonesia's waste crisis, emphasizing the urgent need for effective solutions. Daily waste production, notably in high-producing provinces like Central Java, Jakarta, East Java, West Java, and South Sumatra, has reached alarming levels, totaling 19.6 million tons annually. The study explores the relationship between total waste and recycling rates across provinces, revealing that less than 20% of waste is recycled. Subsequently, a correlation analysis is conducted with the BPS dataset to discern the variables contributing to the elevated waste generation and diminished recycling rate.
Inequality Education in West Java
This project examines the educational landscape of West Java, Indonesia, aiming to address the issue of educational inequality. Despite near-universal access to primary education, disparities persist, particularly affecting children from economically disadvantaged backgrounds. Through a meticulous analysis of school data and leveraging Tableau for visualizations, the project unveils the educational dynamics in West Java. Bandung emerges as a focal point, dominating in terms of the number of schools, especially those with international curricula. The findings underscore the unequal distribution of educational resources, emphasizing the need for expanded access in smaller cities to promote fairness and improve overall education quality in the region.
Credit Card Fraud Detections
Credit card fraud, a widespread issue in payment systems, involves the unauthorized use of payment cards for illicit purposes. This project centers on fraud detection within a dataset containing credit card transactions made by European cardholders in September 2013. The project delves into pre-processing steps, encompassing data cleaning and logistic regression analysis for fraud detection. The statistical overview provides insights into the distribution of normal and fraudulent transactions, emphasizing the critical need for accurate classification due to the significant financial impact of fraud. The analysis highlights the model's performance measures using a confusion matrix, classifying the type I and type II errors, ultimately contributing to a nuanced understanding of fraud detection challenges and opportunities.
Market Reaction to Cigarette Excise Increase Announcement 2019-2022
This project tests two hypotheses and explains the market reaction based on event study methodology, focusing on three prominent companies: Gudang Garam, HM Sampoerna, and Wismilak. The dataset includes historical IHSG data and stocks of the mentioned companies. The t-test, PMF, correlation analysis, and descriptive statistics are used to explain the significance of abnormal returns in influencing investor decisions and shaping market perceptions in response to cigarette excise tax policies. The project offers insights into the market dynamics surrounding cigarette excise tax policies in Indonesia, contributing to a nuanced understanding of investor behavior and market reactions in response to regulatory changes.