Data Analysis Automatic Fare Collection Light Rail Transit Jakarta using the Cluster Method - Mario Hagi; Heri Suroyo; Alek Wijaya; Ahmad Syazili (Universitas Muhammadiyah Sumatera Utara, Indonesia, 2023)
The use of public transportation such as LRT (Light Rail Transit) can reduce the level of congestion in an area and DKI Jakarta is a province with a high level of congestion. The purpose of this study was to determine the general preferences of passengers and to classify stations based on the number of passengers entering-station-exit pairs of the Jakarta LRT by utilizing the cluster analysis method. The data analyzed using the Tableau Desktop application was obtained from the AFC (Automatic Fare Collection) LRT Jakarta. The data contains seven fields, namely PAYMENT METHOD, DATE, TIME OUT, RANGE 60', RANGE 15', STATION OUT, STATION IN for 15 days from 1 January 2023 to 15 January 2023. The results of the study are in the form of data visualization, descriptive statistics, clustering results, and dashboard. Based on the results of the analysis, three clusters were formed with cluster 3 being filled by VEL-BVU and BVU-VEL by controlling 14038 passengers or 40.8% of the total passengers, cluster 2 being filled by VEL-DPD, VEL-BVS, DPD-VEL, and BVS -VEL controlling 10,053 passengers or 29.2% of the total passengers, and the remaining 27 items are in cluster 1 controlling 10,317 passengers or 30.0% of the total passengers.