,
I'm Berlian Muhammad
I am
About Me
I am a data scientist and a fresh graduate with a Bachelor's degree in Informatics. I have extensive experience in using various programming tools, and am proficient in machine learning and deep learning, including the use of libraries such as TensorFlow, Keras, and scikit-learn. With strong analytical skills and problem-solving acumen, I have successfully developed and implemented several projects involving data analysis, prediction, and classification models. I am also an expert in creative and detail-oriented UI/UX design, experienced in designing attractive and functional interfaces.
I keep up to date with the latest developments in data science and technology, and participate in online communities to expand my professional network. With a strong desire to innovate and keep learning, I am ready to contribute to challenging projects. I am eager to work in a collaborative team, and ready to take on roles that can utilize my technical and analytical skills to achieve goals.
Education is the key to unlocking the world wide open, leading us to limitless potential.
Telkom University, Bandung, West Java, Indonesia
SMA N 1 Tegal, Tegal, Central Java, Indonesia
Every project we create is an opportunity to learn, grow, and turn challenges into valuable experiences.
Every life experience, internship and job is a step forward that shapes our success and hones our skills.
Jul 2024 - Aug 2024
Aug 2024 - Present
May 2023 - Present
Oct 2022 - Present
Feb 2023 - Aug 2023
While the achievements are a reflection of dedication and hard work, they are just the beginning of a long journey towards deeper mastery and wisdom.
The research entitled Movie Recommendation System Based on Tweets Using Switching Hybrid Filtering with Recurrent Neural Network was successfully published in a Scopus Q2 indexed journal. The research journal was published in the International Journal of Intelligent Engineering and Systems (IJIES) with an acceptance rate of 14.1%. This achievement is the result of our hard work and dedication who have spent months conducting in-depth research and meticulous manuscript writing. This research focuses on innovations in movie recommendation systems using the Switching Hybrid Filtering approach and Deep Learning Recurrent Neural Network algorithms, successfully attracting the reviewers' attention with significant contributions to the development of science in the field. We hope that the results of this research can contribute a positive impact in the application of technology and become the basis for further research in the future.
