A study on the road accidents using data investigation and visualization in Los Baños, Laguna, Philippines

摘要

Road safety is one of the most vital and crucial part of every countries daily economic growth. It gives so much impact in public health specially in the Philippines. Securing its safety will be a big help to a particular country's economic growth. The main objective of this paper is to analyze road accident's data to discover hidden pattern that can be used as precautionary measure to at least lessen the accident that occur yearly in Los Baños, Laguna, Philippines. Predicting algorithms such as Decision Tree, Naïve Bayes and Rule induction were used to identify factors affecting accident in Los Baños, Laguna. Using these three classifier the following are the results obtained by the researchers; for Decision Tree 92.84% accuracy occurred with 0.797 kappa while in Naïve Bayes 91.50% accuracy was generated with 0.741 kappa and 92.50% accuracy for Rule Induction and 0.783 kappa was produced. The researchers discovered that the place where an accident happened don't have significant correlation on the fatality of the victim. On the other hand, the researchers also found that the time and day play a vital role on the fatality or severity of victims of road accident particularly car collision.