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Journal : IAIC Transactions on Sustainable Digital Innovation (ITSDI)

Experd System of Obesity Diagnosis Using Backward Chaining Method and Certain Factor Fegie Yoanti Wattimena; Reni Koibur; Dion R A Mamisala; Septi Andryana
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 1 No 2 (2020): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v1i2.106

Abstract

Obesity is a medical condition in the form of excess body fat that accumulates in such a way as to have a detrimental impact on health, which then decreases life expectancy and or increases health problems. Obesity is now a common health problem in this modern society with a variety of technological discoveries that make people don't need to move a lot to do something, resulting in people living a lifestyle without much Move. Researchers feel the need for an expert system application that can easily diagnose obesity with everyone just by modalizing simple applications on people's smartphones. The expert system that is built will diagnose early obesity disease by method of drawing inferences using backward chaining method and to test the level of belief conclusions using certainity factor method. The system will be able to provide output in the form of obesity diagnosis, explanation, tips and advice on obesity handling solutions. System development Methods using ESDLC (Expert System Development Life Cycle). The system is built on Android.