Hello
I'm Damar Jati
I'm a UI UX Designer and I love designing beautiful, user-friendly interfaces. I also enjoy working with teams to help them create great user experiences. In my spare time, I like to read, cook, and explore new cities.
My goal is to become a reliable and experienced programmer. I want to be able to develop applications and systems that are innovative and useful for society. I also want to continue learning and improving my skills in technology and programming. And also want to teach programming to children who want to learn to develop their interests and talents in the field of technology.
Strengthened foundational skills in Python programming through the comprehensive Kodland Course. Acquired a deep understanding of software development and coding practices.
Attained expertise in domestic refrigeration during the Refrigeration Vocational program at BBPVP Bekasi. Gained practical experience in the repair and maintenance of refrigeration systems.
Currently pursuing advanced knowledge in web design through the Kodland Course. Developing skills in creating visually appealing and user-friendly web interfaces.
During training at BBPVP Bekasi (July-August 2023), I honed practical skills in repair and maintenance of cooling systems, actively engaging in hands-on practice with refrigerators every day. This experience strengthened my understanding of refrigerator working systems and prepared me for the challenges in the domestic refrigeration industry.
In this project, I designed a user interface (UI/UX) for a login page. The design approach I employ includes elements that are user-friendly, intuitive, and aesthetic. I focused on security and ease of use, resulting in a design that was not only visually appealing but also ensured a seamless user experience during the login process. Implemented features include clear navigation, effective input validation, and integration of security elements to protect user information.
In this task, I use the U-Net model to remove the background from the image. U-Net is a neural network architecture that is effective in image segmentation tasks. I train models with diverse and complex datasets to ensure optimal performance. This implementation allows precise background removal, preserving key object details and improving the quality of the final result.
In this project, I implemented facial object detection using YOLOv5 (You Only Look Once). YOLOv5 is a highly efficient deep learning model for detecting objects in real time. I trained this model with a face-specific dataset and optimized its performance. This implementation enables high-accuracy face identification, even in complex and dense image contexts.
I have designed a user interface (UI/UX) for an authentication page. The main focus is to provide a secure, convenient and user-friendly user experience during the authentication process. This design includes elements such as a two-factor authentication process, clear instructions, and effective error management. I ensured that this design not only met functional needs, but also gave the user a professional and reliable impression.
Our website is under construction but we are ready to go! You can call us or leave a request here.
Want to know more about us, tell us about your project or just to say hello? Drop me a line and I'll get back as soon as possible.
