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Case Study

DiaMate

AI-Powered Diabetes Risk Detection Platform

DiaMate

Description

DiaMate is a web-based platform designed to help users detect early risks of diabetes through a machine learning approach.

By combining AI technology and a user-friendly interface, DiaMate enables users to understand their health conditions earlier and receive recommendations for a healthier and more preventive lifestyle.

Background

Diabetes is one of the growing health problems, including in Indonesia. However, the level of awareness and early detection is still relatively low, especially among young people.

Many individuals are unaware of the risk factors they have due to limited access to easy-to-use and informative detection tools.

DiaMate was developed as a digital solution to provide more accessible, fast, and data-driven risk detection, allowing users to take preventive measures before the condition develops more seriously.

Main Features

  • Interactive self-assessment to collect user health data

  • Prediction of diabetes risk using machine learning models

  • Monitoring dashboard for tracking health data (blood sugar, weight, etc.)

  • Recommendations for activities and lifestyle based on analysis results

  • AI Chatbot for health education and personal interaction

  • Authentication system for a more personal and secure experience

Roles & Contributions

  • Developing the application frontend using Next.js with a focus on user experience

  • Designing the interaction flow (UX flow) to be easily used by various groups

  • Integrating machine learning APIs into the frontend system

  • Building an interactive dashboard display for health data visualization

  • Collaborating in the development of the AI Chatbot feature for user education

  • Optimizing application performance for efficient data processing and presentation

Impact & Results

  • Helping to increase public awareness of diabetes risks

  • Simplifying the early detection process independently and based on data

  • Providing actionable insights for lifestyle changes

  • Presenting a more accessible and user-friendly digital health solution

Tech Stack

Next.jsTailwind.CSSShadcn/UIHapi.jsSupabase