Fruit Ripeness Refrences

Nerva Team - Capstone Projek Bangkit 2021

Overview

In this project we use machine leanring to scanning he fruit for the input then using android for the interface and become the ouput

Explanation

Reason

Fruit is the food we eat most often. Fruit has many nutrients contained in it which is good for us. But sometimes we find it difficult to determine whether the fruit is ripe or not by its colour. So, we come with a simple idea. To give an additional reference for fruit buyer

So our goal in working on this project is so that people can consume fruits at the right time when the nutrients are optimal for our bodies. Determined by the colour. We want our product deliver a same prupose as a ensiklopedia for fruit but using machine learning to ease the user interface, with android for the applications

Result

Our market segmentation is fruit processed consumption, fruit plantation, maerket user, fruit based industry. As for that, we got result is that we achieved our target that we give an additional references to people or segmented user that is ease and reliable to use. Along the way we counter manya chelengged but in the end we managed to completed this capstone project as the result we not fully achieved our target but as the product we want to have a device integrated with the cloud that have same build as the application, just for the scale up

Pressentation submission

• PPT : [link]

Nerva Teams B21-CAP0293

• Android Path
  • Anita Azura (email)
  • Pebi Pebriansah ([email protected])
• Machine Learning Path
  • Alif Lukman Kahfi ([email protected])
  • Rivaldo Yoseph Buarlele ([email protected])
• Cloud Computing Path
  • Mutia Amanda Putri (email)
  • Raynold Panji Zulfiandi (email)