This report was built collaboratively as a real-time monitoring system to track large-scale customer interactions for Transjakarta, encompassing complaints, appreciations, and general inquiries. Due to strict confidentiality agreements, the raw dataset is restricted. Therefore, this summary highlights the structural design and analytical output of the dashboard, which was engineered to monitor Service Level Agreement (SLA) compliance and forecast market sentiment.

Report back-end

Data extraction and processing were executed securely from Transjakarta's internal Google BigQuery data warehouse. Working as part of a collaborative data team, we handled massive volumes of live ticketing data. We ensured strict data integrity and confidentiality while creating an optimized data pipeline ready for real-time visualization.

Report front-end

The interactive dashboard was collaboratively designed in Looker Studio to provide management with immediate visibility into operational bottlenecks. The report focuses on three primary analytical views:

• Real-Time Monitoring - High-level overview of ticketing status and reporting channels.
• Trend & Category Tracking - Time-series analysis for review volumes and SLA fulfillment.
• Strategic Foresight - Predictive sentiment analysis tracking public discourse trajectories.

Real-Time Monitoring features

• Immediate visibility into aggregate ticketing status (Total, Closed, Open, and On SLA).
• Dynamic live filtering by top reporting channels and specific departments, enabling management to isolate and evaluate operational issues swiftly.

Trend & SLA Tracking features

• Time-series visualizations tracking the monthly volume of customer feedback.
• Automated tracking of SLA fulfillment percentages to ensure that passenger complaints and inquiries are resolved within the targeted corporate timeframe.

Strategic Foresight analysis

• By analyzing recent complaint trajectories and sentiment shifts, our team successfully forecasted an imminent spike in negative feedback volume.
• We isolated the root cause of the negative sentiment, identifying that it was heavily driven by emerging public discourse regarding an impending fare increase.