Hi there, I'm Ammar Sufyan

Fresh Graduate Informatics Engineering/Computer Science Student at UIN Syarif Hidayatullah Jakarta, Indonesia.

📝 Skills

Languages

Frameworks

Databases

Tools

Operating Systems

🧷 Connect with me

⚙️ Github Statistics

🎛️ GitHub Profile Stats

🏆 GitHub Trophy

⚡ GitHub Recent Activity

1. ⭐ Starred [gohugoio/hugo](https://github.com/gohugoio/hugo)
2. ⭐ Starred [cvat-ai/cvat](https://github.com/cvat-ai/cvat)
3. ⭐ Starred [xrce/sublie](https://github.com/xrce/sublie)
4. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Copra-YOLOv8-GUI](https://github.com/ammarsufyan/Copra-YOLOv8-GUI)
5. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Copra-YOLOv8-GUI](https://github.com/ammarsufyan/Copra-YOLOv8-GUI)
6. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Copra-YOLOv8-GUI](https://github.com/ammarsufyan/Copra-YOLOv8-GUI)
7. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Coconut-Copra-YOLOv5-GUI](https://github.com/ammarsufyan/Coconut-Copra-YOLOv5-GUI)
8. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Coconut-Copra-YOLOv5-GUI](https://github.com/ammarsufyan/Coconut-Copra-YOLOv5-GUI)
9. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Copra-YOLOv8-GUI](https://github.com/ammarsufyan/Copra-YOLOv8-GUI)
10. ⬆️ Pushed 1 commit(s) to [ammarsufyan/Copra-YOLOv8-GUI](https://github.com/ammarsufyan/Copra-YOLOv8-GUI)

Last Updated: Wednesday, May 15th, 2024, 12:16:42 PM

Ammar Sufyan's Projects

cats-dogs-classification

Classify whether images contain either a dog or a cat.

coconut-copra-yolov5-gui

Coconut and Copra Detection GUI using YOLOv5 models, GUI using Tkinter and OpenCV window.

coconut-quality-classification-streamlit

This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

copra-yolov8-gui

Copra Quality Detection GUI using YOLOv8

darimu

Savings app to make your dreams come true made using c sharp

emailspamdetection-weka

Proyek ini bertujuan untuk memeriksa bahwa email yang diterima adalah spam atau ham melalui klasifikasi teks di WEKA menggunakan algoritma J48 Decision Tree dan Naive Bayes Multinomial Text.