Abstract
Background: Advancements in technology and information a have significantly impacted various aspects of human life, particularly in the realm of transportation. The emergence of a online transportation services has revolutionized commuting habits, offering convenience and accessibility to users. These services encompass two main categories: two-wheeled and four-wheeled vehicles, with online motorcycle taxis being the preferred choice among the public. At Lampung University, a prominent educational institution, the demand for online motorcycle taxi services is notably high due to its status as an educational hub. However, this high level of mobility has led to challenges such as haphazard parking and congestion among online motorcycle taxi drivers. Addressing these issues requires spatial analysis techniques to inform policy-making and alleviate these problems effectively. Methods: This study employs Nearest Neighbor Analysis to assess the distribution pattern of existing online motorcycle taxi pick-up points at Lampung University. Additionally, the suitability of pick-up points is evaluated based on regulatory guidelines and applicator data. Quantitative descriptive research methods are utilized to analyze the collected data and derive insights. Findings: The findings of this research indicate the suitability of online motorcycle taxi pick-up points based on regulatory guidelines and applicator data. The results are presented in the form of suitability tables and distribution maps, highlighting nine suitable locations for pick-up points. Conclusion: The distribution map reveals a random pattern in the arrangement of pick-up points, as determined by the Nearest Neighbor Analysis method. These findings provide valuable insights for stakeholders to formulate policies and strategies aimed at optimizing the management of online motorcycle taxi services at Lampung University.
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