OPTIMALISASI LAYANAN BUS TRANS METRO DELI MEDAN MELALUI CLUSTERING DATA MINING DENGAN METODE PARTITIONING AROUND MEDOIDS

Bus transportation in Indonesia plays a vital role in reducing traffic congestion and supporting sustainable urban mobility. This study aims to optimize the services of Trans Metro Deli Medan by analyzing operational patterns using the Partitioning Around Medoids (PAM) clustering method. The research applies a data mining approach to segment service performance based on passenger volume, travel time, departure frequency, and passenger satisfaction. The analysis results in three distinct clusters: Quiet (average 15 passengers, 38 minutes travel time, low frequency and satisfaction), Medium (50 passengers, 75 minutes, moderate frequency and satisfaction), and Dense (95 passengers, 105 minutes, high frequency and satisfaction). These clusters reveal strong correlations among operational variables and highlight disparities in service quality across routes. Based on the findings, service improvement strategies are proposed: enhancing service quality and visibility for quiet routes, maintaining operational stability for medium routes, and increasing fleet capacity with adjusted scheduling for dense routes. The study demonstrates that PAM clustering provides valuable insights for strategic planning and can significantly contribute to the efficiency and quality improvement of public bus services in Medan.