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Dompet Bijak is a web-based financial management application developed to help users efficiently track their income and expenses. Initially created as a freelance project to assist a student from UPI with their thesis, the application focuses on simplicity and practicality for managing personal finances. The application features a clean and intuitive user interface built using Next.js and Tailwind CSS, providing a responsive and seamless user experience. The backend is powered by Hono API, ensuring fast and reliable data processing. For authentication, the application utilizes Clerk, allowing users to securely log in and manage their financial data. Data storage and management are handled using Neon Database, which offers efficient and scalable solutions for storing transaction records. With Dompet Bijak, users can easily record daily income and expenses, categorize transactions, and view financial summaries to gain better control over their budgeting. This practical tool is designed to empower users in making more informed financial decisions.
Recycle Waste Wisely is a web-based application developed as part of the Orbit Future Academy program. The project aims to promote responsible waste management by providing users with practical guidance on recycling and proper waste disposal. The application features a user-friendly interface that allows users to categorize their waste efficiently. It utilizes data-driven insights to suggest optimal recycling methods based on the type of waste, whether it’s plastic, paper, metal, or organic material. Additionally, users can access educational resources to enhance their knowledge about sustainable practices. One of the standout features of the system is the integration of community-based recycling initiatives, allowing users to collaborate and share tips on waste reduction. The application also tracks user contributions to recycling efforts, fostering a sense of community responsibility. The project incorporates an AI-powered waste classification system, leveraging a trained model using MobileNet V2. This model efficiently classifies different waste types from user-uploaded images, enabling accurate identification and appropriate recycling suggestions. By leveraging modern web technologies and AI integration, Recycle Waste Wisely empowers users to make environmentally conscious decisions, ultimately contributing to a cleaner and greener environment.
The Furniture Sales Information System for CV Rukun Perkasa is a modern web-based application developed to streamline furniture sales and inventory management. The system integrates advanced AI image recognition features to enhance product identification and categorization, significantly improving the efficiency of data entry and inventory tracking. Built using Next.js, the system provides a responsive and user-friendly interface, allowing staff to easily manage product listings, sales transactions, and customer data. The AI image recognition module automatically detects and classifies furniture items from uploaded images, minimizing manual input errors and saving time. Key features of the system include real-time sales reporting, dynamic inventory updates, customer relationship management (CRM), and automated data processing through AI integration. This solution enables CV Rukun Perkasa to optimize sales operations, improve customer engagement, and maintain accurate inventory records. By leveraging cutting-edge web development technologies and AI-driven functionalities, this project has transformed traditional sales processes into a more efficient, tech-driven workflow, aligning with the company’s goals for digital transformation
This certificate is awarded as proof of completing the 'Machine Learning Developer' learning path at IDCamp 2023, at the intermediate level. Throughout this program, I acquired skills in building, training, and evaluating machine learning models using Python and popular ML libraries such as Scikit-learn and TensorFlow. I also gained experience in handling real-world data, performing feature engineering, and implementing supervised and unsupervised learning techniques. This program enhanced my ability to develop practical and efficient machine learning solutions.
This certificate is awarded as proof of completing the 'AI 4 Job' program at Orbit Future Academy as part of the Kampus Merdeka MSIB initiative. In this program, I developed a strong foundation in artificial intelligence (AI) and machine learning (ML) concepts, including data processing, model building, and AI-driven problem-solving. I also gained practical experience in applying AI solutions to real-world scenarios, focusing on industry-relevant skills to enhance employability in the AI field.
his certificate is awarded as proof of completing the Alibaba Cloud Certified Developer program. Through this certification, I gained comprehensive knowledge of Alibaba Cloud services, including computing, storage, database, and networking solutions. I also acquired skills in deploying, managing, and optimizing cloud applications on the Alibaba Cloud platform. This certification demonstrates my proficiency in utilizing cloud technology to develop scalable and reliable applications.
This certificate is awarded as proof of completing the 'Belajar Pengembangan Machine Learning' class at IDCamp. In this class, I learned the fundamental concepts of machine learning, including data preprocessing, model building, and evaluation. I also practiced implementing machine learning algorithms using Python and popular libraries such as TensorFlow and Scikit-learn. The final project involved creating a predictive model to solve real-world problems.
This certificate is awarded as proof of completing the 'Become a React Web Developer Expert' class at Dicoding Indonesia. In this class, I deepened my understanding of advanced concepts in React, including component optimization, state management using Redux, integrating RESTful APIs, and implementing best practices for scalable and maintainable React applications. The final project involved building a dynamic, high-performance web application using modern React libraries and tools.
This certificate is awarded as proof of completing the 'Become a Front-End Web Developer Expert' class at Dicoding Indonesia. The class covers in-depth learning about modern web application development, including understanding React, performance optimization, implementing Progressive Web Apps (PWA), and managing complex state management techniques. Through the final project, I successfully implemented a web application with interactive and responsive features according to industry standards.