Statistical Analysis of Accident Patterns and The Causes at A State Road in Perlis

According to data from the World Health Organization, approximately 1.3 million road users are at high risk of traffic accidents every year. This study aims assess accident patterns and causes on a state between Kangar Alor Setar. The evaluation pattern employed include chi-squared test (CST) level service (LOS) survey. Analysis using Pearson CST reveals that age vehicle type significant factors in accidents. Specifically, individuals below 30 years old have higher likelihood being involved (ρ= 0.037), while motorcycles more prone 0.000). However, gender does not appear impact involvement significantly 0.911). LOS E category indicates unstable flows during Monday Friday evenings. To evaluate perspective users, questionnaire was used, its validity reliability were ensured through pilot study. Four hypotheses developed, examining human factors, environmental condition as independent variables. results reveal majority (33.3%) travel 1 3 times per week, with 23.1% them this road. structural model identifies (t= 6.166, ρ= 0.000), 4.3399, 2.893, 0.005) most contributors Hence, it is crucial for authorities prioritize countermeasures focusing these reduce