Application Of AHP For Determining The Best Of Palm Oil Fresh Fruit Bunch

• Main Author: Norsani, Siti Hadijah
• Format: Thesis
• Language: English; English
• Published: 2016
• Subjects: T Technology (General); TS Manufactures
• Online Access: http://eprints.utem.edu.my/id/eprint/20775/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=104905

This study covers the importance of high quality of palm oil Fresh Fruit Bunches (FFB) to ensure high production in palm oil industry. The level of palm oil FFB maturity will affect to oil extraction rate (OER) which is the main key performance indicator for palm oil industry. The most important process to classify the palm oil FFB ripeness is the grading process. Therefore, the quality grading process of FFB needs to be conducted properly to ensure that high-quality palm oil FFB is selected for production. Usually, the grading process performed by some graders in each mill manually. A sample from each lorry was taken in the grading process. However, this method takes time and may lead to errors in the classification process, especially if the graders have less experience. One of the useful tools that can be employed to make decisions in classification process is Analytical Hierarchy Process (AHP). The main concern was to ensure the reliability of AHP technique achievable. The methodology in this study consists of five phases ie; data collection from expert grader and industries visited, identifying the most important criteria, analysis by AHP method, validation by TOPSIS technique and finally the ranked of the best criteria of high quality FFB. The Expert Choice Software and Microsoft Office Excel are tools that used to analyze the data collected from expert graders in the AHP and TOPSIS technique. The main objective of this study is to determine the best quality of FFB using AHP. The result found that the number of detached fruitlets is the most important criteria to determine the FFB ripeness with 0.560 priority vector followed by color with 0.219 priority vector compared to other criteria. The sensitivity analysis performed to ensure the results are consistent and reliable. It will help the graders to conduct a proper grading process at mills to increase the quality of OER.