Dietry monitoring system using decision tree to control human obesity / Mohamad Faiz Mat Baseri

• Main Author: Mat Baseri, Mohamad Faiz
• Format: Thesis
• Language: English
• Published: 2022
• Subjects: Electronic Computers. Computer Science; Application software; Testing of software; Android; Neural networks (Computer science)
• Online Access: https://ir.uitm.edu.my/id/eprint/58824/1/58824.pdf; https://ir.uitm.edu.my/id/eprint/58824/

Nowadays, obesity is one of the dangerous diseases in the world. Lack of dietary monitoring system will make it difficult for people with obesity to reduce their weight problems. The objective of this project is to develop a dietary monitoring system that can be used by everybody especially for obesity’s people. The method used in this study is to identify the strength and weaknesses of the existing system which involves reviewing some articles, journals, magazines, and books. The survey was conducted which involves 30 people answering the questionnaire. Result from the questionnaire will motivate to developing dietary monitoring system. Next method is utilizing a waterfall model as a method to develop a dietary monitoring system. The system applied the decision tree technique to classified food calorie. It is because each food has different food calories. The last method used in this study involves the participation of three respondents to testing the usability of the system. The results of this study help obesity’s people by developing system for them that can guide to control diet. Significant by developed this system such as helping obesity’s people to diet by giving them the guideline. In conclusion, developing dietary monitoring system will help obesity’s people to control diet.