Hijrah Journey: Al-Qur’an Mobile App

Overview

Hijrah Journey is a Flutter-based mobile app designed to help Muslims deepen their faith amidst their busy daily lives. The app provides easy access to the Quran, prayer schedules, hadiths, and various other worship features—all in one platform.

Tech Stack

• Flutter / Dart — the primary framework for cross-platform UI (Android & iOS)
• Firebase — backend for authentication and data storage
• Muslim Pro API — location-based prayer time data
• Hadith API — hadith database
• Al-Qur’an API — complete Al-Qur’an content

Features

• Read the full Quran with surah navigation
• Automatic prayer schedule based on location
• Prayer time reminders
• Qibla direction finder
• Asmaul Husna (the 99 Names of Allah)
• Collection of hadiths
• Daily prayers
• Prayer intentions
• Digital tasbih

Status

Archived — The project is no longer actively maintained or updated. It was developed as a personal project to explore mobile app development with Flutter and to create a useful tool for Muslims. While the app is available on GitHub, it may not be production-ready or suitable for deployment without further development and testing.

What I Learned

Experience building a feature-rich Flutter app with integration of multiple APIs, efficient state management, and implementation of location-based features and push notifications on mobile platforms.

Dews: Fake News Detection App

Overview

Dews is a hoax news detection website with AI technology. This project was developed as part of the Dews Hackathon, where we aimed to create a tool that can help users identify and filter out fake news from their news feeds. The app uses machine learning algorithms to analyze news articles and determine their credibility based on various features such as source reliability, writing style, and content analysis.

Tech Stack

• Flask — backend framework for serving the hoax detection API
• Pandas — data manipulation and analysis for training the machine learning model
• Numpy — numerical computing for machine learning algorithms
• Laravel — legacy backend components for user management and data storage
• React.JS — frontend framework for building the user interface

Features

• AI-powered hoax news detection based on machine learning models
• User-friendly interface for submitting news articles and viewing results
• Dashboard for monitoring news credibility and trends
• User authentication and profile management
• Integration with external news APIs for real-time analysis

Status

Archived — The project is no longer actively maintained or updated. It was developed as a hackathon project and served as a proof of concept for AI-based hoax detection. While the codebase is available on GitHub, it may not be production-ready or suitable for deployment without further development and testing.

What I Learned

This project provided valuable insights into the challenges of building an AI-powered hoax detection system, including data collection and preprocessing, feature engineering, model training and evaluation, and the importance of user experience in presenting complex AI results in an accessible way. It also highlighted the need for ongoing maintenance and updates to keep such a system effective in the rapidly evolving landscape of online news and misinformation.

GolekFood: Nutrition-Based Food Recommendation App

Overview

GolekFood is an innovative app that provides food recommendations based on nutrition and nutrition integrated with artificial intelligence (AI) technology. Using accurate food data and nutritional information, the app helps users to make healthier food choices that suit their nutritional needs. GolekFood also provides personalization features, allowing users to set their food preferences and obtain recommendations tailored to their health and lifestyle goals. The app focuses on increasing nutrition awareness and making access to nutrition information easier to support users’ healthy lifestyles..

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Tech Stack

• Python — AI model development
• Flask — backend API for serving recommendations
• JavaScript — frontend interactivity and dynamic content
• React JS — frontend framework for building the user interface
• PHP / Laravel — legacy backend components for user management and data storage

Features

• Food recommendation engine based on nutritional content and user preferences
• User profile management with dietary preferences and restrictions
• Integration with external nutrition databases for accurate food information
• Personalized meal planning and recipe suggestions

Status

Archived — The project is no longer actively maintained or updated. It was developed as a proof of concept for a nutrition-based food recommendation system. While the codebase is available on GitHub, it may not be production-ready or suitable for deployment without further development and testing.

What I Learned

This project provided insights into the challenges of building a nutrition recommendation system, including data quality issues, the importance of accurate nutritional information, and the complexities of user personalization in health-related applications.

Water Controller IoT

Overview

Water Controller IoT is a full-stack IoT system that monitors water/soil moisture conditions using sensors. Data from the hardware sensor is sent over the internet to a backend, then displayed in a Flutter mobile app. Users can also remotely control water flow directly from the app based on sensor readings.

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Tech Stack

• Arduino / ESP32 — microcontroller that reads the moisture sensor and communicates with the backend
• Laravel (PHP) — primary REST API for managing IoT-to-app communication and storing sensor data
• Go — alternative API implementation included in the repo
• Flutter / Dart — cross-platform mobile client for monitoring and control
• MySQL — relational database for persisting sensor readings and device state

Features

• Real-time moisture/water level monitoring from hardware sensors
• Remote water flow control via mobile app
• Dashboard view with live sensor data
• List page to browse historical sensor readings
• Add/configure new sensor entries

Challenges

Bridging hardware (Arduino/ESP32) with a web backend required reliable MQTT or HTTP communication, ensuring data consistency even with intermittent device connectivity. The project also includes both a Laravel and a Go API implementation.

Status

Archived — The project is no longer actively maintained or updated. It was developed as a proof of concept for an IoT-based water control system. While the codebase is available on GitHub, it may not be production-ready or suitable for deployment without further development and testing.

What I Learned

End-to-end IoT system design — from firmware on microcontrollers to REST APIs to a mobile frontend. Gained experience with hardware-software integration, sensor data pipelines, and building a multi-layer architecture (embedded → backend → mobile).

Kontennova: WhatsApp and Email Blasting App

Overview

Kontenova is an application for managing blasting scheduled WhatsApp and email messages, built using CodeIgniter 4 and Ajax technology. Its key features include scheduling WhatsApp and email messages, using message templates, customizing scheduling, and providing an intuitive user interface. The app is designed to help users efficiently manage their communication and ensure timely delivery of messages.

Tech Stack

• PHP / CodeIgniter 4 — backend framework for handling business logic and database interactions
• MySQL — relational database for storing message templates, schedules, and user data
• JavaScript / jQuery — frontend interactivity for scheduling and managing messages

Features

• Schedule WhatsApp and email messages for future delivery
• Use message templates for consistent communication
• Customize scheduling with options for one-time or recurring messages
• Intuitive user interface for managing scheduled messages

Status

Internal — This project is an internal application used within the company and is not publicly available. It is actively maintained and updated to meet the communication needs of the organization. The codebase is proprietary and not accessible outside of the company.

What I Learned

This project provided insights into building a scheduling system for communications, including handling time-based triggers, managing message templates, and ensuring reliable delivery of messages. It also highlighted the importance of user experience in designing an intuitive interface for managing scheduled tasks.

POS App: Point of Sale System for Retail Businesses

Overview

This POS (Point of Sale) app is a comprehensive solution designed to streamline sales transactions and inventory management for retail businesses. Built with Node.js and Express.js, the app provides a user-friendly interface for processing sales, managing products, and tracking inventory in real-time. The integration of Tailwind CSS ensures a responsive and visually appealing design, while PostgreSQL serves as the robust database for storing product and transaction data. Additionally, Websocket technology enables real-time updates across multiple devices, making it an efficient tool for retail operations.

POS App

Tech Stack

• Node.js / Express.js — backend framework for handling API requests and business logic
• Tailwind CSS — utility-first CSS framework for building a responsive and modern user interface
• PostgreSQL — relational database for storing product and transaction data
• Websocket — real-time communication for instant updates across devices
• Docker — containerization for easy deployment and scalability

Features

• Product management with CRUD operations
• Sales processing with real-time inventory updates
• User authentication and role-based access control
• Sales reporting and analytics dashboard
• Multi-device support with real-time synchronization

Status

Internal — This project is an internal application used within the company and is not publicly available. It is actively maintained and updated to meet the needs of retail operations. The codebase is proprietary and not accessible outside of the company.

What I Learned

This project provided insights into building a full-stack application with a focus on real-time features and efficient data management. It also highlighted the importance of user experience in designing an intuitive interface for retail staff and the challenges of ensuring data consistency across multiple devices in a real-time environment.