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Transjakarta BRT Analysis

Exploratory data analysis of Transjakarta (Jakarta BRT) transaction data for April 2023: route patterns, peak hours, and passenger demographics.

Unpacked a month of BRT transactions into corridor & peak-hour patterns
PythonPandasJupyterEDAMatplotlibSeaborn

2026-07-27

Concept

Transjakarta is the backbone of Jakarta’s public transport, and its transaction data holds the traces of millions of passenger journeys. This project runs exploratory data analysis (EDA) on April 2023 transaction data to understand how the city actually moves.

Approach

  • Data cleaning: raw transactions normalized, time columns parsed, invalid records dropped.
  • Route analysis: identifying the busiest corridors and trip distribution between stops.
  • Peak hours: mapping hourly passenger surges to reveal the city’s daily rhythm.
  • Demographics: profiling passenger segments from transaction attributes.

Key Findings

Morning and evening peak patterns emerge clearly, with certain corridors dominating trip volume. Demographic analysis reveals the passenger segments most dependent on the BRT.

Reflection

Public transport data is a mirror of the city. Analyzing it isn’t just about numbers; it’s understanding how people move, work, and live within it.