E-ASTEKPAM: Sistem elektronik untuk laporan ASTEKPAM. Cepat, terstruktur, catat unit, tanggal, peralatan, arahan. Fasilitasi transisi keamanan.

Analyzed transaction data from three NYC locations of Maven Roasters to uncover sales patterns and operational efficiencies. Tasks included revenue calculation, date/time extraction, PivotTable creation, and dashboard development. Recommendations were made to optimize operational hours and improve profitability for the Lower Manhattan branch.

This project analyzes ride data and presents interactive visualizations in Power BI. To enhance customer experience and operational efficiency, the company sought insights into how booking confirmations perform during peak and non-peak hours and the impact of outliers on booking outcome times.

AI agent for real-time operational insights. Designed to help industries monitor and improve efficiency using telemetry data and LLM reasoning.

Wind turbine performance analysis using 5-year operational data. Identifies inefficiencies, predicts power output, and provides optimization strategies through machine learning.

Process improvement project to streamline client onboarding and application access. Includes mock SOPs, process maps, and stakeholder feedback templates.

A series of simple-to-advanced analyses on energy usage (kWh) and operational costs for Austin Street Brewery, spearheaded by a collaboration with NEEFC.

Data analysis of physician shift data for hospitals using Google Sheets, featuring data visualization, performance insights, and interactive filters

PubPilot: The Ultimate AI Companion for Bar Management Excellence

This is my Stanford University Code in Place final project code. It is a visualization of some of part of the operations data. The code is written in python.

This project uses vehicle auction data to identify key factors affecting sale prices and auction timelines, uncovering insights and strategies to optimize auction efficiency, inventory management, and overall sales performance.