The Forecasting of a Traffic Accident in the Pandemic of Covid-19
| Main Authors: | Halim, Hasmar, Bustan, Basyar, Saing, Zubair |
|---|---|
| Format: | Article Journal |
| Terbitan: |
, 2021
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/5111107 |
Daftar Isi:
- Speaking of the increase in traffic accidents, transportation safety plays an in important role. This study aims to analyze the number of traffic accidents in Makassar City. On the other hand, the implementation of Large-Scale Social Restrictions (LSSB) to prevent the spread of Covid-19 has an impact on transportation movements in Makassar City. According to this, the traffic accident data used is accident data for 2016 to 2020, which the data for 2020 is data on traffic accidents affected by the LSSB policy. From the results of data analysis, it is known that the accident rate trend tends to follow seasonal patterns so that the model used is the SARIMA Model. Sarima's model with a period (1,1,1) (1,1,1)6 is assumed to be the best model with a MAPE value of 81.6%. Based on the parameters generated by this model, it shows that the number of accidents in 2021 has decreased significantly. This is due to the government policy against the spread of the Covid-19 virus, which is implementing the PSBB. This model cannot be utilized in forecasting for a long period. This is because a long period can cause large estimates that fluctuate in value and even have a tendency for the accident rate to be negative.