Spaces:

feti-ai
/

README

Running

App Files Files Community

README / README.md

faizath

fix: centre the team profile links on the Hugging Face Hub

462c6d9 verified 27 days ago

preview code

Raw

History Blame Contribute Delete

11.3 kB

	---
	title: README
	emoji: 🎲
	colorFrom: indigo
	colorTo: gray
	sdk: static
	pinned: false
	---

	<div align="center">

	# F.E.T.I.

	Faiz · Eleanor · Thalita · Irfan

	Group 16 — two projects in search, optimization, and classification.

	<p>
	<img src="https://img.shields.io/badge/course-IF3070-3b5bdb?style=flat-square" alt="IF3070" style="display:inline-block;vertical-align:middle;margin:0" />
	<img src="https://img.shields.io/badge/institution-STEI%20ITB-1f2937?style=flat-square" alt="STEI ITB" style="display:inline-block;vertical-align:middle;margin:0" />
	<img src="https://img.shields.io/badge/year-2024%2F2025--1-6b7280?style=flat-square" alt="2024/2025-1" style="display:inline-block;vertical-align:middle;margin:0" />
	<img src="https://img.shields.io/badge/group-16-3b5bdb?style=flat-square" alt="Group 16" style="display:inline-block;vertical-align:middle;margin:0" />
	</p>

	</div>

	---

	# Projects

	## Magic Cube Solver

	[![The Magic Cube Solver replaying a search](profile/assets/magic-cube.webp)](https://fetiai.github.io/magic-cube/)

	Six search algorithms racing a 5×5×5 diagonal magic cube — replayed move by move.

	A 5×5×5 diagonal magic cube has 125 cells that must be a permutation of 1..125,
	with all 109 rows, columns, pillars and diagonals summing to 315. Six local-search
	and metaheuristic algorithms attack it server-side in Go, and the browser replays
	the resulting swap log on a scrubber against a live objective-value plot.

	The Genetic Algorithm is the exception. Being a population method it has no single
	sequence of swaps, so it returns no trajectory — the interface charts it rather than
	animating it.

	Algorithms

	`Steepest Ascent Hill Climbing` · `Hill Climbing with Sideways Move` ·
	`Random Restart Hill Climbing` · `Stochastic Hill Climbing` ·
	`Simulated Annealing` · `Genetic Algorithm`

	Built with

	<p>
	<img src="profile/assets/logos/go.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Go
	Fiber
	<img src="profile/assets/logos/svelte.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> SvelteKit
	<img src="profile/assets/logos/threejs.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0;padding:2px;border-radius:3px;background:#fff" /> Three.js
	<img src="profile/assets/logos/chartjs.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Chart.js
	<img src="profile/assets/logos/tailwind.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Tailwind
	<img src="profile/assets/logos/vite.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Vite
	<img src="profile/assets/logos/docker.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Docker
	</p>

	Links — [Live demo](https://fetiai.github.io/magic-cube/) ·
	[Front end](https://github.com/fetiai/magic-cube) ·
	[Solver API](https://github.com/fetiai/magic-cube-core) ·
	[Report (PDF, Indonesian)](https://github.com/fetiai/magic-cube/blob/master/doc/Tubes1_Kelompok16_18222023_18222056_18222059_18222063.pdf)

	---

	## Phishing URL Classifier

	[![The classifier scoring a URL against four models](profile/assets/phishing-url-classifier.webp)](https://phiusiil.faizath.com)

	Two algorithms, each written twice — and the baseline that keeps them honest.

	The UCI PhiUSIIL corpus runs 140,404 URLs deep and only 7.5% of it is hostile —
	which is exactly why accuracy flatters here and recall does the real work. KNN and
	Gaussian Naive Bayes are each built twice across its 49 features, once from scratch
	and once from scikit-learn, so every number has a reference to answer to. Around
	them the pipeline runs EDA, missing-value handling, outlier treatment, feature
	engineering, scaling and SMOTE.

	Dataset: [UCI PhiUSIIL Phishing URL Dataset](https://archive.ics.uci.edu/dataset/967/phiusiil+phishing+url+dataset)
	(repository ID 967). Class 0 is phishing and is the positive class throughout.

	Algorithms

	`K-Nearest Neighbors (from scratch)` · `K-Nearest Neighbors (scikit-learn)` ·
	`Gaussian Naive Bayes (from scratch)` · `Gaussian Naive Bayes (scikit-learn)` ·
	`EDA` · `Feature Engineering` · `SMOTE`

	Results — measured on a 28,081-row validation split.

	\| Model \| Phishing recall \| Accuracy \| F1 \|
	\|---\|---\|---\|---\|
	\| KNN (from scratch) \| 0.759 \| 0.9805 \| 0.856 \|
	\| KNN (scikit-learn) \| 0.763 \| 0.9807 \| 0.859 \|
	\| Gaussian NB (from scratch) \| 0.788 \| 0.9779 \| 0.845 \|
	\| Gaussian NB (scikit-learn) \| 0.888 \| 0.9819 \| 0.883 \|
	\| Baseline — constant "legitimate" \| 0.000 \| 0.9248 \| — \|

	Read every accuracy against that 0.9248 baseline. The corpus is 92.48% legitimate, so
	answering "legitimate" to everything scores 0.9248 while catching no phishing at all —
	which is why phishing recall, not accuracy, is the number that actually moves. The
	held-out file shipped with the dataset has no labels, so there is no test score and
	none is claimed.

	> This is a coursework reimplementation, not a security product. It is trained on a
	> static 2023–24 dataset, has no threat intelligence, no blocklist, and no knowledge of
	> any campaign newer than its training data. Do not use it to decide whether a link is safe.

	Built with

	<p>
	<img src="profile/assets/logos/python.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Python
	<img src="profile/assets/logos/scikit-learn.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> scikit-learn
	<img src="profile/assets/logos/numpy.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> NumPy
	<img src="profile/assets/logos/pandas.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> pandas
	<img src="profile/assets/logos/scipy.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> SciPy
	<img src="profile/assets/logos/streamlit.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Streamlit
	<img src="profile/assets/logos/jupyter.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Jupyter
	<img src="profile/assets/logos/docker.svg" width="18" height="18" align="top" alt="" style="display:inline-block;vertical-align:middle;margin:0" /> Docker
	</p>

	Links — [Live demo](https://phiusiil.faizath.com) ·
	[Repository](https://github.com/fetiai/phishing-url-classifier) ·
	[Report (PDF, Indonesian)](https://github.com/fetiai/phishing-url-classifier/blob/main/doc/Tubes2_Kelompok16_18222023_18222056_18222059_18222063.pdf)

	---

	## Team

	<div align="center">

	<table>
	<tr>
	<td width="220" align="center" valign="top" style="width:220px;text-align:center;vertical-align:top">
	<a href="https://github.com/thalitazhrr" style="display:inline-block">
	<img src="https://github.com/thalitazhrr.png?size=140" width="120" height="120" alt="Thalita Zahra Sutejo" style="border-radius:50%;margin:0" />
	</a>
	<br /><br />
	<b>Thalita Zahra Sutejo</b><br />
	18222023
	<br /><br />
	<a href="https://github.com/thalitazhrr" style="display:inline-block">
	<img src="profile/assets/github.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	thalitazhrr
	</a>
	<br />
	<a href="https://www.linkedin.com/in/thalitazahras/" style="display:inline-block">
	<img src="profile/assets/linkedin.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	thalitazahras
	</a>
	</td>
	<td width="220" align="center" valign="top" style="width:220px;text-align:center;vertical-align:top">
	<a href="https://github.com/IrfanMusthofa" style="display:inline-block">
	<img src="https://github.com/IrfanMusthofa.png?size=140" width="120" height="120" alt="Irfan Musthofa" style="border-radius:50%;margin:0" />
	</a>
	<br /><br />
	<b>Irfan Musthofa</b><br />
	18222056
	<br /><br />
	<a href="https://github.com/IrfanMusthofa" style="display:inline-block">
	<img src="profile/assets/github.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	IrfanMusthofa
	</a>
	<br />
	<a href="https://www.linkedin.com/in/irfanmusthofa/" style="display:inline-block">
	<img src="profile/assets/linkedin.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	irfanmusthofa
	</a>
	</td>
	<td width="220" align="center" valign="top" style="width:220px;text-align:center;vertical-align:top">
	<a href="https://github.com/EleanorCordelia" style="display:inline-block">
	<img src="https://github.com/EleanorCordelia.png?size=140" width="120" height="120" alt="Eleanor Cordelia" style="border-radius:50%;margin:0" />
	</a>
	<br /><br />
	<b>Eleanor Cordelia</b><br />
	18222059
	<br /><br />
	<a href="https://github.com/EleanorCordelia" style="display:inline-block">
	<img src="profile/assets/github.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	EleanorCordelia
	</a>
	<br />
	<a href="https://www.linkedin.com/in/eleanorcordelia/" style="display:inline-block">
	<img src="profile/assets/linkedin.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	eleanorcordelia
	</a>
	</td>
	<td width="220" align="center" valign="top" style="width:220px;text-align:center;vertical-align:top">
	<a href="https://github.com/faizath" style="display:inline-block">
	<img src="https://github.com/faizath.png?size=140" width="120" height="120" alt="Muhammad Faiz Atharrahman" style="border-radius:50%;margin:0" />
	</a>
	<br /><br />
	<b>Muhammad Faiz Atharrahman</b><br />
	18222063
	<br /><br />
	<a href="https://github.com/faizath" style="display:inline-block">
	<img src="profile/assets/github.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	faizath
	</a>
	<br />
	<a href="https://www.linkedin.com/in/faizath/" style="display:inline-block">
	<img src="profile/assets/linkedin.svg" width="14" height="14" alt="" style="display:inline-block;vertical-align:middle;margin:0" />
	faizath
	</a>
	</td>
	</tr>
	</table>

	</div>

	---

	<div align="center">

	IF3070 Foundations of Artificial Intelligence · STEI ITB · 2024/2025-1

	More at [fetiai.github.io](https://fetiai.github.io/)

	</div>