Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir
Road accident is a major problem in society because it obviously quite happens every day and occurs in Kelantan. This study focus about the number of road accident during festive season in Kota Bharu, Kelantan from the year 2015 to 2017 and the accident victim whose ages are in between 18 and 55 yea...
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| Format: | Student Project |
| Language: | English |
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Faculty of Computer and Mathematical Sciences, UiTM Perlis
2019
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| Online Access: | http://ir.uitm.edu.my/id/eprint/25415/ http://ir.uitm.edu.my/id/eprint/25415/1/PPb_NABILA%20MAT%20NASIR%20CS%20R%2019_5.pdf |
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uitm-25415 |
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eprints |
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uitm-254152019-09-11T08:46:50Z http://ir.uitm.edu.my/id/eprint/25415/ Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir Mat Nasir, Nabila Traffic accidents Fuzzy decision making Road accident is a major problem in society because it obviously quite happens every day and occurs in Kelantan. This study focus about the number of road accident during festive season in Kota Bharu, Kelantan from the year 2015 to 2017 and the accident victim whose ages are in between 18 and 55 years old including females and males. The objectives are to forecast the number of road accidents in Kelantan during festive seasons by using the fuzzy time series, to compare the number of road accidents in Kelantan during festive seasons and normal season. In this study the application of fuzzy time series is used to predict the number of road accident during festive season. This study also used error measure Mean Absolute Scale Error (MASE) to determine the fuzzy time series is accurate to use in forecasting. Besides, if value of MASE is greater than one so that the method is not good while the value of error measure is less than one so that the prediction is better. Since the value of MASE is 0.0820 less than one, therefore the method is good to use in order to forecasting the number of road accident during festive seasons in Kota Bharu Kelantan and would help “Polis Diraja Malaysia” (PDRM) to solve the problem. This study would be advantageous to drivers if they obey the rules set out and are aware about road accidents and drive carefully. PDRM would also give some exposure to road users, so can increase their knowledge on road law and third parties have the responsibility to educate them to increase their awareness in this issue. Faculty of Computer and Mathematical Sciences, UiTM Perlis 2019-08-30 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/25415/1/PPb_NABILA%20MAT%20NASIR%20CS%20R%2019_5.pdf Mat Nasir, Nabila (2019) Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir. [Student Project] (Unpublished) |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Teknologi MARA |
| building |
UiTM Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
Traffic accidents Fuzzy decision making |
| spellingShingle |
Traffic accidents Fuzzy decision making Mat Nasir, Nabila Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| description |
Road accident is a major problem in society because it obviously quite happens every day and occurs in Kelantan. This study focus about the number of road accident during festive season in Kota Bharu, Kelantan from the year 2015 to 2017 and the accident victim whose ages are in between 18 and 55 years old including females and males. The objectives are to forecast the number of road accidents in Kelantan during festive seasons by using the fuzzy time series, to compare the number of road accidents in Kelantan during festive seasons and normal season. In this study the application of fuzzy time series is used to predict the number of road accident during festive season. This study also used error measure Mean Absolute Scale Error (MASE) to determine the fuzzy time series is accurate to use in forecasting. Besides, if value of MASE is greater than one so that the method is not good while the value of error measure is less than one so that the prediction is better. Since the value of MASE is 0.0820 less than one, therefore the method is good to use in order to forecasting the number of road accident during festive seasons in Kota Bharu Kelantan and would help “Polis Diraja Malaysia” (PDRM) to solve the problem. This study would be advantageous to drivers if they obey the rules set out and are aware about road accidents and drive carefully. PDRM would also give some exposure to road users, so can increase their knowledge on road law and third parties have the responsibility to educate them to increase their awareness in this issue. |
| format |
Student Project |
| author |
Mat Nasir, Nabila |
| author_facet |
Mat Nasir, Nabila |
| author_sort |
Mat Nasir, Nabila |
| title |
Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| title_short |
Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| title_full |
Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| title_fullStr |
Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| title_full_unstemmed |
Forecasting the number of road accident during festive season in Kelantan using fuzzy time series / Nabila Mat Nasir |
| title_sort |
forecasting the number of road accident during festive season in kelantan using fuzzy time series / nabila mat nasir |
| publisher |
Faculty of Computer and Mathematical Sciences, UiTM Perlis |
| publishDate |
2019 |
| url |
http://ir.uitm.edu.my/id/eprint/25415/ http://ir.uitm.edu.my/id/eprint/25415/1/PPb_NABILA%20MAT%20NASIR%20CS%20R%2019_5.pdf |
| first_indexed |
2023-09-18T23:14:41Z |
| last_indexed |
2023-09-18T23:14:41Z |
| _version_ |
1777419033500450816 |