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●​ Built a REST API using Flask (Python) and Mask R-CNN for instance segmentation to detect and count
fruits from images of trees captured in the field.
●​ Integrated OpenCV for image preprocessing to optimize inference results and detection accuracy.
●​ Developed a cross-platform Flutter mobile app enabling field operators to securely log in, capture or
upload tree images, and view the counted results in real time.
●​ Implemented seamless API communication with backend services and real-time visual feedback on
detected fruit instances.
●​ Developed supporting backend services (user management, task tracking) using Go (Iris framework)
with PostgreSQL for reliable and scalable data storage.
Technologies : Python (Flask), Mask R-CNN, OpenCV, Dart (Flutter), Go (Iris), PostgreSQL, REST API,
Mobile-AI Integration

●​ Developed a REST API using Flask (Python) integrated with YOLOv8 segmentation to identify and
segment algae in uploaded images.
●​ Utilized OpenCV for image preprocessing to improve detection accuracy and ensure consistent input
quality.
●​ Built a native Android application in Kotlin that allows users to securely log in, upload images, and view
detection results with visual overlays and metadata.
●​ Ensured efficient end-to-end communication between the mobile app and the AI backend, with a focus
on responsiveness and usability for field researchers or environmental engineers.
Technologies: Python (Flask), YOLOv8 Segmentation, OpenCV, Android (Kotlin), REST API, Mobile-AI
Integration

Developed an end-to-end intelligent bacteria detection platform combining AI, mobile interfaces, and RESTful
services to support scientific research and clinical diagnostics.
●​ Designed and deployed a YOLOv8-powered REST API using Flask (Python) to detect bacterial
presence in microscope images, with preprocessing handled via OpenCV for optimal model input.
●​ Built a cross-platform mobile application using Flutter, enabling secure user login, image uploads, and
real-time display of detection results.
●​ Developed a user management module (authentication, authorization, user profiles) as a REST API
service using Go (Iris Framework) for high-performance handling.
●​ Integrated PostgreSQL as the central relational database, ensuring data consistency between AI results,
user actions, and application logs.
●​ Engineered seamless communication between frontend and backend systems, providing a fluid user
experience for researchers and healthcare professionals.
Technologies: Python (Flask), YOLOv8, OpenCV, Dart (Flutter), Go (Iris), PostgreSQL, REST API, Mobile AI
Integration

●​ Developed a Web Application that store and manage all official documents in the form of incoming and
outgoing letters
●​ Developed a REST API to view the document on Android and send notification to Android app
●​ Developed Android App that can view the document and receive notification from server when there is a
new document arrived
Technologies : Node JS / Express JS, Java for Android, Onesignal for push notification,PostgreSQL,
Bootstrap

Developed a high-performance backend system to integrate PERURI’s E-Meterai (official Indonesian digital
stamp) issuance into SkillAcademy.com, a large-scale online learning platform with high daily traffic.
●​ Designed and implemented a robust Spring Boot REST API to generate and validate E-Meterai
documents securely and efficiently.
●​ Introduced a connection pool management system to ensure stability and scalability during peak traffic,
handling thousands of concurrent requests.
●​ Optimized performance and fault tolerance for third-party API communication with PERURI.
●​ Ensured data integrity and traceability using PostgreSQL for persistent storage and transactional
consistency.
Technologies: Java, Spring Boot, REST API, Connection Pooling, PostgreSQL, E-Meterai Integration,
High-Traffic API Design

Designed and developed an end-to-end breast cancer detection solution combining computer vision, deep
learning, and mobile accessibility to assist early diagnosis from medical images.
●​ Built a RESTful API using Flask (Python) that integrates YOLOv8 and OpenCV to detect breast cancer
from uploaded images with high accuracy.
●​ Preprocessed and analyzed medical imagery using OpenCV to enhance model detection performance.
●​ Developed a cross-platform Flutter mobile application allowing users to capture or upload images and
view detection results with clear visual feedback.
●​ Engineered smooth client-server interaction, securely sending images to the API and displaying
bounding boxes and classifications in real-time.
●​ Ensured efficient image handling, model inference, and response time optimization for practical mobile
usage.
Technologies: Python (Flask), YOLOv8, OpenCV, Dart (Flutter), REST API, Mobile-Computer Vision Integration

Built a modern, cross-platform mobile Point of Sale (POS) system from scratch, combining powerful backend
services with a sleek mobile interface to streamline in-store transactions and inventory management.
●​ Frontend (React Native + Expo)
○​ Developed a mobile-first POS interface with React Native (Expo) for both Web and Android
○​ Implemented barcode scanning using the device camera via expo-barcode-scanner and
supported manual barcode input fallback.
○​ Built dynamic cart management and real-time order updates using Zustand state management.
○​ Designed intuitive UI/UX with React Navigation, Vector Icons, Toast Messages, and ChartKit for
analytics.
○​ Implemented secure authentication using Clerk for React Native and Expo Secure Store.

●​ Backend (Node.js + TypeScript + Express)
○​ Created RESTful APIs using TypeScript, Express, and Drizzle ORM for PostgreSQL.
○​ Used clerk/express for secure API access and user management
Technologies: Express JS, React Native, Expo, TypeScript, Clerk, Zustand, neon.tech, Stripe, React Navigation
Github: https://www.twine.net/signin

Built a full-featured Point of Sale (POS) system with a Spring Boot backend and Angular frontend. The
backend, developed in Java 17, leverages Spring Boot 3.1, Spring Security with JWT for authentication,
and Spring Data JPA with MySQL for database operations. RESTful APIs are documented using
SpringDoc OpenAPI and automatically consumed by the Angular frontend via OpenAPI Generator,
ensuring type-safe API integration
The Angular app, built with Angular 17, incorporates advanced UI components using PrimeNG, ag-Grid,
and Bootstrap 5, with secure JWT-based login powered by https://www.twine.net/signin This project showcases
end-to-end full stack integration, automated client code generation, and modern architecture practices
for scalable, maintainable retail solutions.
Technologies: Java 17, Spring Boot 3.1, Spring Security (JWT), Spring Data JPA, RESTful APIs, OpenAPI
(Swagger), Angular 17, TypeScript, HTML5, CSS3, Bootstrap 5, PrimeNG, ag-Grid, MySQL, JPA/Hibernate,
Lombok, OpenAPI Generator, RxJS, JWT, Maven
Github: https://www.twine.net/signin