Abstract
This paper presents the assessment of a number of factors affecting bus travel time and a relationship model between those factors and bus travel time. Statistica Neural Network (SNN) tool is used to solve this complex phenomenon. Data collected include bus travel time, distance, average speed, and number of bus stop. The results show that bus travel time is well predicted using variables of distance, average speed, and number of bus stops. The bus travel time increased due to the increase of distance and number of bus stops, while the higher the average speed from one stop to another, the lower bus travel time. Keywords: bus travel time prediction, distance, average speed of bus, number of bus stop
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