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All Journal Mandalika Mathematics and Educations Journal
Siti Alfiatur Rohmaniah
Universitas Islam Darul’ Ulum
Mathematics

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Model Regresi Quasi Poisson Jumlah Korban Kecelakaan Lalu Lintas di Kabupaten Lamongan Galuh Nadiya Nurfaiza; Awawin Mustana Rohmah; Siti Alfiatur Rohmaniah
Mandalika Mathematics and Educations Journal Vol 8 No 2 (2026): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i2.12119

Abstract

Traffic accidents are one of the major transportation safety problems that may cause casualties and material losses. Analysis of the number of accident victims is important to describe accident severity and identify influencing factors. This study aims to model the number of traffic accident victims in Lamongan Regency based on time characteristics and road conditions using Quasi Poisson regression. The data used were secondary data obtained from the Lamongan Police consisting of 1,202 traffic accident observations during 2025. The analysis stages included descriptive analysis, Poisson regression modeling, dispersion testing, and Quasi-Poisson regression modeling. The dispersion test result showed a dispersion parameter value of 0.4161, indicating underdispersion where the variance was smaller than the mean. This condition caused the standard Poisson regression model to be less appropriate because the equidispersion assumption was not fulfilled. The Quasi Poisson model produced more reliable statistical inference by adjusting the variance through a dispersion parameter. The significant variables affecting the number of traffic accident victims were month, day category, road status, and road condition. Therefore, the Quasi Poisson regression model was more suitable for modeling underdispersed traffic accident count data.
Pemodelan Regresi Logistik Biner terhadap Tingkat Keparahan Kecelakaan Lalu Lintas di Kabupaten Lamongan Kurnia Indah Wulandari; Siti Alfiatur Rohmaniah; Mohammad Syaiful Pradana
Mandalika Mathematics and Educations Journal Vol 8 No 2 (2026): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i2.12121

Abstract

Abstract Traffic accidents are a transportation safety issue that have significant social and economic impacts. This study aims to analyze the factors influencing traffic accident severity in Lamongan Regency using binary logistic regression. The data used were secondary data on 1,206 traffic accident cases from 2024 obtained from the Lamongan Police. The response variables were classified into two categories: minor accidents and serious accidents. Predictor variables included the number of fatalities, the number of minor injuries, the time of the accident, the type of accident, the cause of the accident, the road status, the road condition, and the road type. The analysis was conducted using binary logistic regression with a stepwise variable selection method based on the Akaike Information Criterion (AIC). The results showed that the number of fatalities, the number of minor injuries, the time of the accident, the type of accident, the road status, and the road type significantly influenced traffic accident severity. The resulting model achieved a classification accuracy of 78.11%, enabling a reasonably good classification of accident severity.
Co-Authors Awawin Mustana Rohmah Galuh Nadiya Nurfaiza Kurnia Indah Wulandari Mohammad Syaiful Pradana