Inference Analysis of Dry Rubber Content Capacitance Properties in Discriminating Type of Rubber Clones / Ummu Raihan Yussuf...[et al.]

• Main Authors: Yussuf, Ummu Raihan (Author), Hashim, Hadzli (Author), Johari, Juliana (Author), Mohd Sampian, Ahmad Faiz (Author), Abdullah, Noor Ezan (Author), Khairuzzaman, Noor Aishah (Author), Maskom, Mohamad Azrif (Author)
• Format: Book
• Published: Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), 2017.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/38469/1/38469.pdf
• Keywords: TJ Mechanical engineering and machinery

This project describes the development of a capacitive sensor for measuring capacitance of the Dry Rubber Content (DRC) by using parallel plate for classification of rubber clones. Five dry rubber contents from different clones were identified: RRIM2002, RRIM2007, RRIM2008, RRIM2014 and RRIM3001. An aluminium tape had been used as a parallel plate sensor and paired with Arduino microcontroller for the output extraction. The device measures the output in capacitance value from the capacitance sensor based on the dry rubber content samples placed in between the two plates. Statistical analysis using the SPSS software is used to analyse data for each rubber clone; in which for discrimination of data, the normality distribution was tested. The analysis of normality revealed that the data is not normally distributed. Thus, non-parametric test Kruskal-Wallis test is used. Result shows that there is a statistical significance difference of the capacitance value among the five different rubber clone groups. This is proven by significant level of Kruskal-Wallis test of less than 0.05. RRIM2002 has the highest mean rank of capacitance value followed by RRIM2008, RRIM2014, RRIM3001 and the lowest is RRIM2007.