A hybrid approach to modelling the climate change effects on Malaysia's oil palm yield at the regional scale

• Main Authors: Shanmuganathan, S (Author), Narayanan, A (Author), Mohamed, M (Author), Ibrahim, R (Author), Haron, K (Author)
• Format: Others
• Published: Soft Computing and Data Mining (SCDM), University Tun Hussein Onn, Malaysia, 2014-03-24T18:51:14Z.
• Subjects: Regression test; Data mining (association rules); WEKA; JRip; Conference Contribution
• Online Access: Get fulltext
• Item Description: The First International Conference on Soft Computing and Data Mining (SCDM 2014) held at Universiti Tun Hussein Onn Malaysia (UTHM), Johor, Malaysia, 2014-06-16to 2014-06-18

Understanding the climate change effects on local crops is vital for adapting new cultivation practices and assuring world food security. Given the volume of palm oil produced in Malaysia, climate change effects on oil palm phenology and fruit production have greater implications at both local and international scenes. In this context, the paper looks at analysing the recent climate change effects on oil palm yield within a five year period (2007-2011) at the regional scale. The hybrid approach of data mining techniques (association rules) and statistical analyses (regression) used in this research reveal new insights on the effects of climate change on oil palm yield within this small data set insufficient for conventional analyses on their own