Snapnutrition as education and nutrition improvement for Indonesian people through machine learning technology / Akhmad Lazuardi ... [et al.]

The making of this work aims to solve the problem of nutrition in Indonesia. Because in 2017 babies under the age of five who experience nutritional problems reach 17.8%. Plus the breadth of the Indonesian territory is also a barrier for the government to educate the public about balanced nutrition. However, the spread of internet infrastructure in Indonesia through the Palapa Ring project has been 77% in the central region, 46% in the eastern region and at the end of 2019 it is targeted to be completed. This indicates that our work will be beneficial to the existence of such infrastructure to improve nutrition in Indonesia. With the internet infrastructure and the development of Machine Learning technology we collaborate on these technologies. We use Machine Learning because the technology can recognize food and then provide the nutrient content in the food. Plus the cultural conditions that are very prural so that many culinary treasures that cause if using human power will take a long time. We also add nutritional data on each food and the people can also contribute to adding nutritional data as well, which of course will be filtered first by machine learning. With this, the people is also expected to be educated on the importance of maintaining nutrition in every food. In the future, we expect the importance of Snapnutrition as a tool to educate people who are difficult to reach and also as a reminder that the people is maintaining nutrition in every food so that health is maintained and also preparing healthy Indonesian children to meet 100 years of Indonesian independence.