Recently Published

Time Series Analysis of Monthly Precipitation in Pennsylvania
The time series data that I have chosen to analyze is the Monthly Precipitation in Pennsylvania over a span of 150 years. This data is provided by the [National Centers for Environmental Information](https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/statewide/time-series/36/pcp/1/3/1895-2025). The purpose for this data being collected is to track and monitor climate and precipitation trends. This helps support research that is related to weather forecasting and public safety. Since precipitation is a critical variable in studying the ever changing climate, knowing the long term trends in precipitation totals will impact how agriculture, infrastructure, and water sources function. This will help services plan around different events such as droughts, floods, or normal precipitation.
Low Wage Map
Low Wage Map
session_228
Fixed \alpha in all rounds, deterministic energy price, table version (no risk, no loss), cost treatment
Missing value, data duplikat, outlier & inkonsistensi data
Proses identifikasi dan penanganan missing value, deteksi outlier menggunakan metode statistik, serta pembersihan data duplikat dan inkonsistensi data. Menggunakan R dan packages dplyr, tidyr.
ARCHI RMU Relief Portal Dashboard: Analysis of Housing Assistance Applications in Metro Atlanta (Mar–Oct 2025)
This interactive dashboard analyzes applications submitted through the ARCHI RMU Relief Portal between March and October 2025. The analysis examines trends in housing assistance requests across Metro Atlanta, including rent and utility support needs, geographic disparities by ZIP code, and monthly demand patterns. Using data exported from the Salesforce RMU portal (28,875 cleaned records), the dashboard highlights neighborhoods with the highest need, identifies seasonal surges in assistance requests, and illustrates the gap between applicant demand and available funding through community-based organization (CBO) partners. This work was completed as part of the Applied Practice Experience (APE) for the MPH program at the Rollins School of Public Health, Emory University. The dashboard was developed using R (Flexdashboard, Plotly, and DT) to support data-driven decision-making and resource targeting for housing stability initiatives.