CeritaKita - Mental Health Support Platform
An AI-integrated mental health platform built with Kotlin & Jetpack Compose, providing counseling services, journaling, and self-help tools.
Timeline
Q1 2024 - Q3 2024
Tech Stack
Kotlin (Jetpack Compose) - Android Development, Firebase Authentication - Secure Login, Google Cloud Firestore - Database, Retrofit - API Integration, FastAPI - AI Model API, Jetpack Navigation - App Flow Management
Overview
Developed during Bangkit 2024, CeritaKita is an AI-powered mental health app designed to provide accessible, affordable, and stigma-free mental health support for Indonesian users. The platform allows users to track their emotional well-being, book counseling sessions, and access self-help resources. Built entirely with Kotlin & Jetpack Compose, the app integrates AI-based emotion recognition and counselor recommendations via backend APIs. The project was proposed for 140 million IDR in funding and is positioned as a scalable solution to Indonesia’s mental health challenges.
Features
Journaling & Self-Help Tools
Users can track emotions, write daily reflections, and access mental health guides.
Session Booking System
Seamlessly schedule counseling with professionals or peer mentors.
AI Integration for Emotion Detection
Backend API integration for text & image-based emotion analysis.
Personalized Counselor Matching
AI-driven recommendations based on user needs.
Secure Authentication
Firebase Authentication for user login and data security.
Cloud-Connected Infrastructure
Uses Google Cloud Firestore for real-time data management.
Objectives
- •Develop a Kotlin-based Android application with Jetpack Compose for a modern UI experience.
- •Integrate AI-powered emotion recognition and counselor recommendations via backend APIs.
- •Implement secure authentication & session management using Firebase.
- •Ensure a smooth and intuitive user experience for booking counseling sessions.
Challenges & Solutions
Challenge 1
Integrating AI-powered emotion recognition seamlessly into the mobile app.
Solution
Used Retrofit to connect with the FastAPI-based ML API, ensuring real-time data processing.
Challenge 2
Building a responsive UI with Jetpack Compose for various screen sizes.
Solution
Implemented adaptive layouts and Material 3 components for a modern user experience.
Challenge 3
Ensuring secure authentication and session management.
Solution
Used Firebase Authentication with token-based access control for user data security.
Results
Proposed funding for platform development. (Rejected—guess investors weren’t ready for AI-powered therapy)
Project completed in under 2 months with positive user feedback.
Integrated session booking, journaling, and authentication.
Key Learnings
This project reinforced my expertise in Kotlin, Jetpack Compose, and Firebase integration. The experience of working with AI-powered APIs also improved my skills in backend API communication and secure session management.