Numerical modelling for caterers’ grading system in Pahang
Background: The hygiene level of the premise reflect the safety and quality of the food served in the food services kitchen and the poor sanitary condition can contribute to food poisoning outbreaks. Recently, many food poisoning cases reported from food services sector and most of the cases are fro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Quality Scientific Publishng
2018
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/63983/ http://irep.iium.edu.my/63983/ http://irep.iium.edu.my/63983/1/29580%20Published%20May%202018%20Amran.pdf |
| Summary: | Background: The hygiene level of the premise reflect the safety and quality of the food served in the food services kitchen and the poor sanitary condition can contribute to food poisoning outbreaks. Recently, many food poisoning cases reported from food services sector and most of the cases are from institutional food services. These premises sometimes are graded as clean or very clean which can be questioned, mostly at institutions such as schools. Objectives: The aim of this research is to establish mathematical models using multiple linear regression (MLR) technique to determine the food safety level and premise grading of active caterers in Pahang State, using artificial neural network. Methods: In this research, the premises have been categorised into 3 categories namely institutional, event caterers and premise at Rest and Rescue Area (RnR) along the East Coast Highway. A total of 268 premises were involved in this study with 139 (51.87%) institutional, 63 (23.51%) event caterers and 66 (24.63%) RnR. The instrument used in this research is based on the official risk based premise inspection form currently used by Ministry of Health Malaysia. The important focusing items in the inspection form are process control, building and facilities, equipment and utensils, cleaning and maintenance, as well as food handler’s requirements. These items consist of a total thirty (31) elements with respected weight age score based on risk to food safety. In this research, stepwise method is used where several significant models will be developed. Results: The results show that the best and significant model is the 33rd model where the independent variables explain 100% of the dependent variables (R-square=1.00, p-val=0.00). Conclusion: As a conclusion, it is expected that this system will help the related authorities by confirming national standards and create more uniformity in catering inspections. In the future, it is suggested that the result can be improved by revising Part A: Process Control, in the Malaysian premise inspection form where the elements should be elaborated more details by comparing to the ones used in other countries |
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