Application of Artificial Intelligence SSD MobileNet and Tiny YOLOv2 for Food Recipe Search

Abstract

Recipes are guides to making something together with notes on ingredients and their amount. To be able to make food, of course, the cook must prepare the ingredients in advance to be processed into ready-to-eat dishes. Often people have a lot of food ingredients but don't know how to process them. Cooking without seriousness, of course, some people fail when making a dish. Back then, people depends on recipe that was passed down from generation to generation. Now, the digital world is growing rapidly. Anything can be done with increasingly modern technology. Everything needed is accessible with today's technology. Everything is so easy, including the matter of food. Even so, in this digital era, people use smartphones but still cannot use them properly. Many of them use search engines so they need to sort out which are real recipes and which are just random recipes. The purpose of this study is to help people find recipes by taking photos of food ingredients and then finding out what can be made from these ingredients. This technique uses Artificial Intelligence (AI) with MobileNet and Tiny YOLOv2 SSD modules. The design uses the Unified Modeling Language (UML). The study used experimental methods to test the accuracy of the AI used. Data collection will be utilizing a literature study. This research uses agile for system development. Test results show that the SSD MobileNet model has a guessing accuracy of 77%, while Tiny YOLOv2 is 81%. The guessing accuracy might get higher if good camera quality is used