Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi
The aim of this study is to investigate factors that significantly contribute to death of the driver in an accident. For the purpose of this study, a total of 200 dataset was collected from the accident cases reported in News Straits Times occurred throughout Malaysia during 2nd of January 2018 u...
| Main Author: | |
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| Format: | Student Project |
| Language: | English |
| Published: |
Faculty of Computer and Mathematical Sciences
2018
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/26865/1/Pbb_MUHAMMAD%20SHAFIQ%20AZEMI%20CS%20R%2019_5.pdf |
| _version_ | 1796902393303007232 |
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| author | Azemi, Muhammad Shafiq |
| author_facet | Azemi, Muhammad Shafiq |
| author_sort | Azemi, Muhammad Shafiq |
| collection | UITM |
| description | The aim of this study is to investigate factors that significantly contribute to death of the
driver in an accident. For the purpose of this study, a total of 200 dataset was collected
from the accident cases reported in News Straits Times occurred throughout Malaysia
during 2nd of January 2018 until 20th of October 2018. This research study applies
Logistic Regression technique by using SPSS software to analyze the results. The
variables or factors studied involved several dichotomous variables such as the type of
driver’s vehicle, the gender of the driver, the status of the driver, the state where the
accidents occurred, the time and the cause of the accident. In general, road condition,
weather condition and drug abuse are not the major factors that leads to driver’s fatal
accident. Furthermore, there are only two significant variables which act as a good
predictor for the model namely the time of accident in the afternoon as well as gender. |
| first_indexed | 2024-03-06T02:04:16Z |
| format | Student Project |
| id | uitm.eprints-6865 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:04:16Z |
| publishDate | 2018 |
| publisher | Faculty of Computer and Mathematical Sciences |
| record_format | dspace |
| spelling | uitm.eprints-68652020-03-19T08:00:42Z https://ir.uitm.edu.my/id/eprint/26865/ Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi Azemi, Muhammad Shafiq Computer software The aim of this study is to investigate factors that significantly contribute to death of the driver in an accident. For the purpose of this study, a total of 200 dataset was collected from the accident cases reported in News Straits Times occurred throughout Malaysia during 2nd of January 2018 until 20th of October 2018. This research study applies Logistic Regression technique by using SPSS software to analyze the results. The variables or factors studied involved several dichotomous variables such as the type of driver’s vehicle, the gender of the driver, the status of the driver, the state where the accidents occurred, the time and the cause of the accident. In general, road condition, weather condition and drug abuse are not the major factors that leads to driver’s fatal accident. Furthermore, there are only two significant variables which act as a good predictor for the model namely the time of accident in the afternoon as well as gender. Faculty of Computer and Mathematical Sciences 2018-01 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/26865/1/Pbb_MUHAMMAD%20SHAFIQ%20AZEMI%20CS%20R%2019_5.pdf Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi. (2018) [Student Project] (Unpublished) |
| spellingShingle | Computer software Azemi, Muhammad Shafiq Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title | Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title_full | Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title_fullStr | Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title_full_unstemmed | Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title_short | Determining significant factors that leads traffic drivers to fatal accidents in Malaysia by using : Logistic Regression / Muhammad Shafiq Azemi |
| title_sort | determining significant factors that leads traffic drivers to fatal accidents in malaysia by using logistic regression muhammad shafiq azemi |
| topic | Computer software |
| url | https://ir.uitm.edu.my/id/eprint/26865/1/Pbb_MUHAMMAD%20SHAFIQ%20AZEMI%20CS%20R%2019_5.pdf |
| work_keys_str_mv | AT azemimuhammadshafiq determiningsignificantfactorsthatleadstrafficdriverstofatalaccidentsinmalaysiabyusinglogisticregressionmuhammadshafiqazemi |