Final Year Informatics Student based in Yogyakarta, Indonesia. I have a strong interest in technology, product development, data analysis, and software engineering. Constantly seeking new challenges and opportunities to learn and grow in my field.
<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/33f8438e-7eca-4ba1-856c-33922936035a/bxl-linkedin.svg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/33f8438e-7eca-4ba1-856c-33922936035a/bxl-linkedin.svg" width="40px" /> Linkedin
</aside>
<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/37d2f83c-ac0a-462d-a6ef-65adf7eecac7/25231.png" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/37d2f83c-ac0a-462d-a6ef-65adf7eecac7/25231.png" width="40px" /> thoriqfy
</aside>
<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/4203e3ff-3cc1-4cf6-a5e3-b955099c4d00/bxl-instagram-alt.svg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/4203e3ff-3cc1-4cf6-a5e3-b955099c4d00/bxl-instagram-alt.svg" width="40px" /> @thoriq.fy
</aside>
Feb 2023 - Jul 2023 | Indonesia, Singapore
Providing data analysis in a visual manner, insights, and recommendation around metrics performance, which are used by business users (executives, product managers) to make data-driven decisions.
Nov 2021 - Jan 2022 | Yogyakarta
Responsible for creating bash scripts to automate the database inventory flow, creating an ETL schema using the Hgrid247 platform, and creating server virtualization using the Proxmox platform.
Oct 2021 - Jun 2022 | Yogyakarta
Writing content on daily issues using data-driven knowledge and visualize it in a beautiful way. We focus on instagram @datadotjpg
2019 - Information Engineering
My final thesis focuses on the use of deep learning techniques for emotional classification. Specifically, I trained a deep learning model on a dataset of labeled emotional expressions and used this model to classify emotions in new data. The results of this work demonstrate the potential of deep learning for accurately identifying emotions in visual and textual data, and could have applications in fields such as psychology and natural language processing.
