Optimalisasi Waktu Penjemputan Dan Lokasi Pada Data Histori Perjalanan NYC TLC Menggunakan Exploratory Data Analysis
DOI:
https://doi.org/10.61132/uranus.v1i2.175Keywords:
univariate analysis, NYC TLC, taxi usage patternsAbstract
This study analyzes the "NYC TLC Trip Record" dataset for the period January 1, 2023 to January 31, 2023 to understand taxi usage patterns in New York City. The objectives to be achieved in this analysis include: (1) Identify the days and times with the highest demand for taxi services, (2) Identify the boroughs with the highest demand for taxi services. We applied univariate analysis for this analysis. The results show that the day with the highest demand occurs on Tuesday for the densest time occurs in the vulnerable time of 3 pm to 6 pm. The boroughs with the highest taxi demand are Manhattan, Queens, and Brooklyn. This analysis provides the results for NYC TLC to develop a data-driven optimization strategy. This analysis not only helps in identifying demand hotspots but also provides insights for more efficient taxi scheduling and placement. With this analysis, it is expected that more effective pick-up time and location optimization strategies can be developed, thereby improving operational efficiency and customer satisfaction in taxi services in New York City.
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