Forecasting natural rubber price in Malaysia using Arima
This paper contains introduction, materials and methods, results and discussions, conclusions and references. Based on the title mentioned, high volatility of the price of natural rubber nowadays will give the significant risk to the producers, traders, consumers, and others parties involved in t...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7061/ http://eprints.uthm.edu.my/7061/1/P10211_63e00e5c8fee0600086202fb3063e334.pdf |
| _version_ | 1848888989860233216 |
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| author | Zahari, Fatin Z. Khalid, Kamil Roslan, Rozaini Sufahani, Suliadi Mohamad, Mahathir Rusiman, Mohd Saifullah Ali, Maselan |
| author_facet | Zahari, Fatin Z. Khalid, Kamil Roslan, Rozaini Sufahani, Suliadi Mohamad, Mahathir Rusiman, Mohd Saifullah Ali, Maselan |
| author_sort | Zahari, Fatin Z. |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | This paper contains introduction, materials and methods, results and discussions,
conclusions and references. Based on the title mentioned, high volatility of the price of
natural rubber nowadays will give the significant risk to the producers, traders, consumers,
and others parties involved in the production of natural rubber. To help them in making
decisions, forecasting is needed to predict the price of natural rubber. The main objective of
the research is to forecast the upcoming price of natural rubber by using the reliable statistical
method. The data are gathered from Malaysia Rubber Board which the data are from January
2000 until December 2015. In this research, average monthly price of Standard Malaysia
Rubber 20 (SMR20) will be forecast by using Box-Jenkins approach. Time series plot is used
to determine the pattern of the data. The data have trend pattern which indicates the data is
non-stationary data and the data need to be transformed. By using the Box-Jenkins method,
the best fit model for the time series data is ARIMA (1, 1, 0) which this model satisfy all the
criteria needed. Hence, ARIMA (1, 1, 0) is the best fitted model and the model will be used
to forecast the average monthly price of Standard Malaysia Rubber 20 (SMR20) for twelve
months ahead. |
| first_indexed | 2025-11-15T20:19:03Z |
| format | Conference or Workshop Item |
| id | uthm-7061 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:19:03Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-70612022-05-24T01:47:39Z http://eprints.uthm.edu.my/7061/ Forecasting natural rubber price in Malaysia using Arima Zahari, Fatin Z. Khalid, Kamil Roslan, Rozaini Sufahani, Suliadi Mohamad, Mahathir Rusiman, Mohd Saifullah Ali, Maselan T Technology (General) This paper contains introduction, materials and methods, results and discussions, conclusions and references. Based on the title mentioned, high volatility of the price of natural rubber nowadays will give the significant risk to the producers, traders, consumers, and others parties involved in the production of natural rubber. To help them in making decisions, forecasting is needed to predict the price of natural rubber. The main objective of the research is to forecast the upcoming price of natural rubber by using the reliable statistical method. The data are gathered from Malaysia Rubber Board which the data are from January 2000 until December 2015. In this research, average monthly price of Standard Malaysia Rubber 20 (SMR20) will be forecast by using Box-Jenkins approach. Time series plot is used to determine the pattern of the data. The data have trend pattern which indicates the data is non-stationary data and the data need to be transformed. By using the Box-Jenkins method, the best fit model for the time series data is ARIMA (1, 1, 0) which this model satisfy all the criteria needed. Hence, ARIMA (1, 1, 0) is the best fitted model and the model will be used to forecast the average monthly price of Standard Malaysia Rubber 20 (SMR20) for twelve months ahead. 2018 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/7061/1/P10211_63e00e5c8fee0600086202fb3063e334.pdf Zahari, Fatin Z. and Khalid, Kamil and Roslan, Rozaini and Sufahani, Suliadi and Mohamad, Mahathir and Rusiman, Mohd Saifullah and Ali, Maselan (2018) Forecasting natural rubber price in Malaysia using Arima. In: ISMAP 2017, October 28, 2017, Batu Pahat, Johor. https://doi.org/10.1088/1742-6596/995/1/012013 |
| spellingShingle | T Technology (General) Zahari, Fatin Z. Khalid, Kamil Roslan, Rozaini Sufahani, Suliadi Mohamad, Mahathir Rusiman, Mohd Saifullah Ali, Maselan Forecasting natural rubber price in Malaysia using Arima |
| title | Forecasting natural rubber price in Malaysia using Arima |
| title_full | Forecasting natural rubber price in Malaysia using Arima |
| title_fullStr | Forecasting natural rubber price in Malaysia using Arima |
| title_full_unstemmed | Forecasting natural rubber price in Malaysia using Arima |
| title_short | Forecasting natural rubber price in Malaysia using Arima |
| title_sort | forecasting natural rubber price in malaysia using arima |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/7061/ http://eprints.uthm.edu.my/7061/ http://eprints.uthm.edu.my/7061/1/P10211_63e00e5c8fee0600086202fb3063e334.pdf |