Predicting Olympic Medal Trends for Southeast Asian Countries Using the Facebook Prophet Model
The Olympics is a world sporting event held every four years and is a meeting place for all athletes worldwide. The Olympics are held alternately in different countries. The Olympics were first held in Athens in 1896 and have now reached the 33rd Olympics, which will be held in Paris in 2024. A lot...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Islam Negeri Sunan Kalijaga Yogyakarta
2025-01-01
|
| Series: | JISKA (Jurnal Informatika Sunan Kalijaga) |
| Subjects: | |
| Online Access: | https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/4825 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The Olympics is a world sporting event held every four years and is a meeting place for all athletes worldwide. The Olympics are held alternately in different countries. The Olympics were first held in Athens in 1896 and have now reached the 33rd Olympics, which will be held in Paris in 2024. A lot of work has been done to develop prediction models emphasizing improving accuracy to predict Olympic outcomes. However, low-performance regression algorithms are the main problems with prediction. By integrating custom seasonality with the Facebook-Prophet prediction model, this study aims to increase the accuracy of Olympic prediction. The proposed new model involves several steps, including preparing the data and initializing and fitting the Facebook-Prophet model with several parameters such as seasonal mode, annual seasonality, and prior scale. The model is tested using the Olympic dataset (1994–2024). The evaluation results show that this prediction model can provide a good value in predicting the total medals earned. On the Olympic Games (1994-2024) dataset, the model has a very low error MAE, MSE, and RMSE and has an R2 score of 0.99, which is close to perfect. This research shows that the model is effective in improving prediction accuracy.
|
|---|---|
| ISSN: | 2527-5836 2528-0074 |