Forem: Muhammad Dhiyaul Atha

I Built a Safety-First Workflow Layer for Pacman (ATHA)

Muhammad Dhiyaul Atha — Tue, 31 Mar 2026 16:35:36 +0000

Managing packages on Arch Linux is powerful, but sometimes it lacks visibility and safety.

You run a command… and it just executes.

No preview. No clear audit trail. No structured workflow.

So I started building ATHA — a safety-first workflow layer on top of pacman.

What is ATHA?

ATHA is not a replacement for pacman.

It tries to enhance it with:

Install planning (--plan) before execution
Dry-run support for safer operations
Confirmation layers for critical actions
Operation history with timeline view
Built-in system diagnostics (atha doctor)

The goal is simple:

Make package operations more predictable, transparent, and auditable.

Example

Before installing a package:

atha install --plan neovim

You get a preview of:

dependencies
disk usage
source (official repo or AUR)

Why I Built This

Arch gives full control — but sometimes operations can feel a bit “blind”.

ATHA is my attempt to improve:

Safety → reduce accidental changes
Transparency → understand what will happen
Auditability → keep track of what happened

Comparison

Feature	pacman	yay	ATHA
Dry-run support	❌	❌	✅
Install planning	❌	❌	✅
Operation history	❌	❌	✅
Workflow consistency	❌	❌	✅

Installation

yay -S atha

💬 Feedback

This project is still evolving and definitely not perfect.

I’m sure there are things that can be improved — both in design and implementation.

If you have feedback, criticism, or suggestions, I’d really appreciate hearing them.

My First Attempt at Building a Reasoning AI (ARC Prize 2026)

Muhammad Dhiyaul Atha — Thu, 26 Mar 2026 07:28:57 +0000

What if AI fails the moment the problem changes?

Most AI systems today are great at recognizing patterns — but what happens when the problem itself is different from anything they’ve seen before?

That’s exactly the challenge behind the ARC Prize 2026 on Kaggle.

Getting Started

I recently joined the ARC-AGI-2 competition on Kaggle, which challenges participants to build AI systems capable of solving problems they’ve never seen before.

Unlike typical machine learning tasks, ARC is not about training on massive datasets.

Instead, it focuses on something closer to human intelligence:
reasoning and generalization.

My First Approach (Baseline)

To get started, I built a very simple baseline model.

The goal was not to solve the problem yet — but to:

Understand the dataset structure
Learn how submissions work
Successfully make my first submission

Here’s the basic idea:

Read input grid
Generate output grid with the same shape
Fill it with zeros

Yes — it's intentionally simple.

Code & Repository

You can check my first implementation here: https://github.com/Bangkah/arc-agi-learning

This repository documents my learning journey as I explore reasoning-based AI.

First Submission (Kaggle)

Why Start Simple?

Because ARC is not about jumping into complex models.

It’s about:

Understanding transformations
Identifying patterns
Building logic step-by-step

Even advanced AI systems still struggle with ARC tasks.

Why ARC is Hard

ARC tasks require:

Understanding abstract patterns
Applying transformations
Generalizing from very few examples

Unlike traditional machine learning, there is no training phase with millions of samples.

Each problem is a completely new challenge.

First Submission Result

My first submission didn’t perform well — and that’s expected.

The real goal was:
✔ Understanding the pipeline
✔ Getting familiar with the problem
✔ Starting the journey

Key Insight

ARC is fundamentally different from most AI challenges.

It’s not about:
❌ memorizing patterns

It’s about:
✔ discovering rules
✔ applying logic
✔ adapting to new problems

What’s Next?

My next steps:

Solve ARC tasks manually
Build rule-based solutions
Improve generalization step-by-step

💡 Final Thoughts

This is not just a competition — it’s a challenge to rethink how we approach AI.

And I’m just getting started.

Have you tried solving ARC tasks?

I’d love to hear how others approach reasoning problems like this.

[Boost]

Muhammad Dhiyaul Atha — Tue, 24 Mar 2026 04:53:53 +0000

Muhammad Dhiyaul Atha

Mar 24

My First Home Server Using a 12-Year-Old Laptop

#linux #devops #productivity #homelab

Comments

2 min read

My First Home Server Using a 12-Year-Old Laptop

Muhammad Dhiyaul Atha — Tue, 24 Mar 2026 04:41:31 +0000

When an Old Laptop Finds Its New Purpose

Turning a 2012 MacBook Pro into My First Personal Server

There was a 2012 MacBook Pro sitting in front of me.

Not my main machine anymore.
Definitely not fast by today’s standards.

But that’s exactly where a simple question came up:

“How far can this old laptop still be useful?”

That question led me to a small experiment —
turning this old machine into a personal server and controlling it remotely via SSH from my main laptop.

Why an Old Laptop?

As a software engineering student, I started realizing something important:

Learning about servers is not enough if it’s only theory.

I can read documentation, watch tutorials, and follow guides —
but there’s always a gap between knowing and actually experiencing it.

At the same time, I had:

A 2012 MacBook Pro collecting dust
A growing interest in Linux
Curiosity about how servers actually work

So instead of letting it sit unused, I turned it into a learning lab.

System Choice: Arch Linux on Old Hardware

I chose Arch Linux for this machine.

Not because it’s easy — actually the opposite.

But because I wanted:

A lightweight system
Full control over everything installed
A raw, hands-on learning experience

For my main laptop, I use an Acer Nitro V16 running Garuda Linux —
this is where I control everything from.

The Struggles: Nothing Worked Perfectly

Of course, things didn’t go smoothly at first.

Here are some challenges I faced:

⚠️ Old hardware limitations (heat, performance)
⚠️ Arch Linux setup complexity
⚠️ Networking confusion (IP, services, firewall)
⚠️ SSH failing due to small misconfigurations

There were frustrating moments, especially when:

“Why is SSH installed but I still can’t connect?”

But those were the moments where real learning happened:

Reading logs
Understanding errors
Not just copy-pasting commands

The Goal: More Than Just Remote Access

My goal wasn’t just:

“Connect via SSH from another laptop”

I wanted to:

Understand how servers actually work
Get comfortable working without a GUI
Simulate a simple backend/DevOps workflow
Build the habit of working remotely

This server became my personal lab —
a safe place to break things and learn.

The Breakthrough Moment

The most satisfying moment?

From my main laptop, I ran:

ssh atha@192.xxx

And then…

The terminal of the 2012 MacBook appeared on my screen.

No GUI.
No mouse.
Just a terminal.

But it felt like opening a door to a completely new world.

What I Can Do Now

Now I can:

Manage my server from my main laptop
Install and configure services remotely
Bring an old machine back to life

And this is just the beginning.

Next, I plan to explore:

Setting up a web server
Building a simple API
SSH hardening
Small automation scripts

Final Thoughts

This experiment taught me something important:

Learning servers doesn’t have to be expensive.

Sometimes, an old laptop and curiosity are enough.

That 2012 MacBook Pro that once felt outdated
now has a new role.

Not as my main machine —
but as a silent teacher, helping me understand systems, patience, and real learning.

And this journey…

is just getting started 🚀

What about you?
Have you ever repurposed old hardware into something useful?

Saya Membuat CLI Tool Jadwal Shalat dan Merilisnya ke Arch Linux AUR

Muhammad Dhiyaul Atha — Wed, 18 Feb 2026 12:30:23 +0000

Sebagai pengguna Linux dan seseorang yang sering bekerja di terminal, saya ingin bisa melihat jadwal shalat langsung dari CLI tanpa membuka browser atau aplikasi GUI.

Dari kebutuhan sederhana itu, saya membuat sebuah tool bernama jadwal-shalat — sebuah CLI tool profesional berbasis Python yang dapat menampilkan jadwal shalat secara otomatis berdasarkan lokasi pengguna.

Sekarang tool ini sudah tersedia secara resmi di Arch Linux AUR.

Latar Belakang

Banyak aplikasi jadwal shalat tersedia, tapi sebagian besar berbasis:

Mobile apps
Website
Aplikasi GUI

Masalahnya, bagi pengguna Linux yang sering bekerja di:

terminal
server
SSH session
environment minimal

solusi tersebut tidak praktis.

Saya ingin sesuatu yang:

ringan
cepat
otomatis
dan native di terminal

Maka saya membuat CLI tool ini.

Apa Itu jadwal-shalat?

jadwal-shalat adalah CLI tool Python yang dapat:

mendeteksi lokasi otomatis dari IP publik
menentukan timezone secara akurat
mengambil jadwal shalat dari API Aladhan (method Kemenag Indonesia)
menampilkan jadwal secara rapi di terminal

Tool ini dirancang khusus untuk pengguna Indonesia.

Fitur Utama

Beberapa fitur yang tersedia saat ini:

Deteksi IP publik otomatis
Deteksi lokasi otomatis (kota, negara, koordinat, timezone)
Fallback API lokasi jika layanan utama gagal
Menggunakan API Aladhan (method=20/Kemenag Indonesia)
Jadwal shalat lengkap
Menampilkan waktu shalat berikutnya + countdown
Output terminal rapi dengan alignment yang baik
Error handling lengkap
Timeout protection untuk API
Support timezone akurat
Siap packaging AUR dengan auto update

Contoh Output

Contoh ketika dijalankan:

Output difokuskan agar:

mudah dibaca
minimalis
profesional
cocok untuk penggunaan harian di terminal

Instalasi via Arch Linux AUR

Tool ini sekarang tersedia di AUR, sehingga instalasi sangat mudah:

yay -S jadwal-shalat

Atau manual:

git clone https://aur.archlinux.org/jadwal-shalat.git
cd jadwal-shalat
makepkg -si

Sebagai maintainer AUR, saya juga mengatur auto-update menggunakan GitHub Actions.

Instalasi Manual

Jika tidak menggunakan Arch Linux:

pip install requests

Clone repo:

git clone https://github.com/Bangkah/jadwal-shalat.git
cd jadwal-shalat
chmod +x jadwal-shalat.py
./jadwal-shalat.py

Atau:

python jadwal-shalat.py

Cara Kerja Tool Ini

Secara sederhana:

Mengambil IP publik user
Mengubah IP menjadi lokasi geografis
Menentukan timezone
Mengambil jadwal shalat dari API Aladhan
Menampilkan jadwal dan countdown

Semua proses dilakukan secara otomatis.

Fokus pada Reliability

Beberapa hal yang saya implementasikan untuk memastikan tool stabil:

fallback API jika layanan lokasi gagal
timeout protection
error handling jaringan
parsing timezone akurat
output formatting konsisten

Ini penting agar tool tetap berfungsi bahkan dalam kondisi jaringan tidak stabil.

Integrasi dengan Arch Linux Packaging

Salah satu milestone terbesar project ini adalah berhasil dipublish ke Arch Linux AUR.

Ini berarti:

user bisa install dengan yay
update terdistribusi secara otomatis
mengikuti standar packaging Linux
tool menjadi lebih profesional

Saya juga mengintegrasikan GitHub Actions untuk membantu workflow update.

Roadmap ke Depan

Beberapa fitur yang direncanakan:

input manual kota
input manual koordinat
output JSON
notifikasi waktu shalat
packaging PyPI

Tujuannya adalah membuat tool ini semakin fleksibel.

Kenapa Saya Membuat Project Ini?

Selain kebutuhan pribadi, project ini juga menjadi sarana belajar tentang:

CLI development dengan Python
API integration
timezone handling
Linux packaging (PKGBUILD)
AUR maintenance
CI/CD dengan GitHub Actions

Project kecil seperti ini sangat membantu meningkatkan skill sebagai developer.

Open Source dan Kontribusi

Project ini open source dan tersedia di GitHub:

https://github.com/Bangkah/jadwal-shalat

Kontribusi sangat diterima.

Penutup

Linux memiliki ekosistem CLI yang sangat kuat, dan saya percaya tool kecil seperti ini bisa meningkatkan produktivitas pengguna terminal.

Jika kamu pengguna Arch Linux atau Linux secara umum, kamu bisa mencoba tool ini dan memberikan feedback.

Building Sentinel AI: A Cybersecurity CLI Powered by Copilot

Muhammad Dhiyaul Atha — Sat, 14 Feb 2026 17:30:38 +0000

From Copilot Experiment to Production-Ready CLI: Building Sentinel AI

Cybersecurity is no longer optional — every connected system is exposed to potential threats. While there are many enterprise-grade tools available, I wanted to understand how such tools work internally.

So I built my own.

Sentinel AI started as a small experiment using GitHub Copilot CLI. But through iteration, debugging, and production hardening, it evolved into a fully functional, production-ready cybersecurity CLI tool for Linux.

This article explains the journey — from idea to production.

The Idea

Modern systems constantly create network connections — many legitimate, some suspicious. Most users never see what is happening behind the scenes.

I wanted a tool that could:

Show active network connections
Identify suspicious behavior
Assign risk scores
Provide actionable summaries
Work directly from the terminal

It needed to be fast, simple, and transparent.

That’s how Sentinel AI was born.

How GitHub Copilot Accelerated Development

GitHub Copilot CLI significantly accelerated development by helping generate:

Modular Python code structure
CLI argument parsing using argparse
Risk classification logic
Error handling and logging
Clean and readable code patterns

Instead of spending hours writing boilerplate, I could focus on architecture and functionality.

Copilot acted as a coding assistant — not a replacement — helping me move faster while maintaining control over the system design.

Architecture Overview

Sentinel AI is built using a modular architecture:

Core components:

Network Scanner — collects active connections
Analyzer — evaluates connections and assigns risk scores
Reporting Engine — summarizes system risk level
CLI Interface — provides user interaction
Logging System — records activity and errors

Key technologies:

Python
psutil
colorama
argparse
autopep8
GitHub Actions (CI/CD)

This architecture ensures maintainability and extensibility.

Core Features

Sentinel AI provides several security-focused capabilities:

Network Scanning

Lists all active network connections with:

Protocol
Local address
Remote address
Process ID
Process name

Example:

sentinel-ai scan

Intelligent Risk Analysis

Each connection is analyzed and assigned:

Numeric risk score (0–100)
Risk level classification:
- LOW
- MEDIUM
- HIGH
Explanation of the risk

Example:

sentinel-ai analyze

Example output:

Proto  Local Address      Remote Address     PID   Process   Risk
TCP    192.168.1.10:54321 8.8.8.8:53        1234  python3   HIGH (87)

System Risk Report

Provides a system-level security overview:

sentinel-ai report

Output:

=== Sentinel AI CLI Security Report ===
Total connections: 12
External connections: 3
High risk: 1
Medium risk: 2
Low risk: 9
Overall system risk: HIGH (72/100)

This allows users to understand their system security posture instantly.

System Information

Displays system-level information:

sentinel-ai system

Includes:

OS
Kernel version
CPU
Memory
Hostname

Developer Utilities

Sentinel AI also includes developer-focused tools:

sentinel-ai debug file.py
sentinel-ai explain-code file.py
sentinel-ai improve-code file.py

These tools help developers analyze, debug, and improve Python code.

From Prototype to Production

What started as a simple script evolved into a production-grade CLI tool.

Key improvements included:

Modern Python Packaging

Sentinel AI uses:

pyproject.toml
Standardized project structure
Proper dependency management

CI/CD Pipeline

Using GitHub Actions, Sentinel AI now has automated:

Linting (PEP8 compliance)
Build validation
Test execution
Release safety checks

This ensures every update maintains production quality.

Trusted Publishing to PyPI

Sentinel AI uses secure Trusted Publishing, allowing automated and secure package releases.

This eliminates manual credential handling and improves release security.

Installation

Sentinel AI is available on PyPI.

Install using:

pip install sentinel-ai-cli

Run:

sentinel-ai report

And immediately see your system’s security overview.

Challenges and Lessons Learned

Building Sentinel AI taught me several important engineering lessons:

1. CI/CD Discipline

Fixing lint errors, formatting issues, and pipeline failures helped reinforce professional development practices.

2. Production Packaging

Using modern Python packaging standards improved maintainability and reliability.

3. CLI Design Principles

Designing a clean CLI interface requires careful planning to ensure usability and clarity.

4. Copilot as a Force Multiplier

Copilot accelerated development — but debugging and refinement required human understanding.

AI helped build faster, but engineering discipline made it production-ready.

Future Plans

Planned improvements include:

Arch Linux (AUR) package
Docker image
Real-time monitoring mode
Threat intelligence integration
Plugin system

Sentinel AI will continue evolving.

Open Source and Availability

GitHub Repository:
https://github.com/Bangkah/sentinel

PyPI Package:
https://pypi.org/project/sentinel-ai-cli/

Sentinel AI is fully open source and contributions are welcome.

Conclusion

Sentinel AI began as a simple experiment with GitHub Copilot CLI.

Through iteration, debugging, CI/CD integration, and proper packaging, it became a production-ready cybersecurity tool.

This project demonstrates how modern AI-assisted development, combined with engineering discipline, can accelerate the creation of real-world tools.

Sentinel AI is not just a project — it is a foundation for building more advanced security tools in the future.

Author

Muhammad Dhiyaul Atha
Computer Science Student & Open Source Developer

Saat Laptop Lama Menemukan Peran Barunya

Muhammad Dhiyaul Atha — Fri, 30 Jan 2026 18:11:37 +0000

Mengubah MacBook Pro 2012 Menjadi Server Pribadi (Eksperimen Pertamaku)

Ada satu MacBook Pro 2012 di hadapanku.
Bukan laptop utama, performanya juga jelas sudah tertinggal jauh dibanding mesin-mesin modern. Tapi justru dari situ muncul satu pertanyaan sederhana:

“Sejauh apa laptop lama ini masih bisa berguna?”

Pertanyaan itu akhirnya membawaku pada sebuah eksperimen kecil: mengubah MacBook Pro 2012 menjadi server pribadi, lalu mengontrolnya dari laptop utamaku menggunakan SSH.

Latar Belakang: Kenapa Laptop Lama?

Sebagai mahasiswa dan pembelajar di dunia software engineering, aku mulai sadar satu hal:
belajar server tidak cukup hanya dari teori.

Aku bisa membaca dokumentasi, menonton video, atau mengikuti tutorial, tapi tetap ada jarak antara “tahu” dan “pernah mengalami sendiri”.

Di sisi lain, aku punya:

MacBook Pro 2012 yang jarang dipakai
ketertarikan besar pada Linux
rasa penasaran tentang bagaimana server bekerja di dunia nyata

Daripada membiarkannya berdebu, aku memutuskan menjadikannya server eksperimen.

Pilihan Sistem: Arch Linux di Mesin Tua

Aku memilih Arch Linux untuk MacBook Pro 2012 ini.

Bukan karena paling mudah — justru sebaliknya.
Tapi karena aku ingin:

sistem yang ringan
kontrol penuh terhadap apa saja yang terpasang
dan pengalaman belajar yang “apa adanya”

Untuk laptop utamaku, aku menggunakan Acer Nitro V16 dengan Garuda Linux. Dari sinilah semua kontrol dilakukan.

Kendala: Tidak Semua Berjalan Mulus

Tentu saja, eksperimen ini tidak langsung berjalan mulus.

Beberapa kendala yang aku temui:

⚠️ Hardware lama: kipas cepat panas, performa terbatas
⚠️ Konfigurasi Arch Linux yang menuntut ketelitian
⚠️ Networking yang awalnya membingungkan (IP, service, firewall)
⚠️ SSH yang sempat gagal konek karena kesalahan kecil

Ada momen frustrasi, terutama saat:

“Kenapa sudah install SSH tapi tetap tidak bisa diakses?”

Namun justru di titik-titik inilah aku benar-benar belajar:
membaca log, memahami error, dan tidak asal copy–paste perintah.

Tujuan: Bukan Sekadar Bisa Remote

Tujuanku bukan hanya:

“bisa login SSH dari laptop lain”

Lebih dari itu, aku ingin:

memahami konsep server secara nyata
membiasakan diri mengelola sistem tanpa GUI
mensimulasikan workflow backend & DevOps sederhana
dan melatih kebiasaan bekerja secara remote

Server ini aku anggap sebagai laboratorium pribadi, tempat aman untuk salah dan belajar.

Progres: Saat SSH Akhirnya Berhasil

Momen paling memuaskan adalah saat dari Acer Nitro V16 aku menjalankan:

ssh atha@192.xxxx

Lalu…
terminal MacBook Pro 2012 muncul di layarku.

Tidak ada tampilan grafis.
Tidak ada mouse.
Hanya terminal — tapi rasanya seperti membuka pintu ke dunia baru.

Sekarang aku bisa:

mengelola server dari laptop utama
install service tanpa menyentuh fisik server
menjadikan MacBook lama sebagai mesin yang “hidup kembali”

Dari sini, rencananya akan berlanjut ke:

web server
API sederhana
hardening SSH
dan mungkin automasi kecil-kecilan

Penutup

Eksperimen ini mengajarkanku satu hal penting:

Belajar server tidak harus mahal.
Kadang, laptop lama dan rasa penasaran sudah cukup.

MacBook Pro 2012 yang dulu terasa usang, kini punya peran baru.
Bukan sebagai mesin utama, tapi sebagai guru diam-diam yang mengajarkanku tentang sistem, kesabaran, dan proses belajar yang sebenarnya.

Dan perjalanan ini… baru saja dimulai.

Membuat API CRUD di Laravel dengan Sanctum (Step by Step)

Muhammad Dhiyaul Atha — Sun, 11 Jan 2026 15:00:37 +0000

"Pernah nggak, frontend kamu butuh data dari backend Laravel, tapi API-nya belum aman? Di artikel ini, kamu akan belajar bikin API CRUD yang hanya bisa diakses user terautentikasi pakai Sanctum."

Kenapa Harus Pakai Sanctum untuk API CRUD?

Data lebih aman, hanya user login yang bisa akses
Cocok untuk SPA, mobile app, dan aplikasi modern
Mudah diintegrasikan dengan frontend (React, Vue, dsb)

Studi Kasus: API Artikel (CRUD + Auth)

Kita akan membuat API CRUD Artikel yang hanya bisa diakses user yang sudah login menggunakan Laravel Sanctum.

Step 1: Setup Project Laravel & Sanctum

composer create-project --prefer-dist laravel/laravel belajar-api
cd belajar-api
composer require laravel/sanctum
php artisan vendor:publish --provider="Laravel\Sanctum\SanctumServiceProvider"
php artisan migrate

Tambahkan middleware Sanctum di app/Http/Kernel.php pada group api:

'api' => [
    \Laravel\Sanctum\Http\Middleware\EnsureFrontendRequestsAreStateful::class,
    'throttle:api',
    \Illuminate\Routing\Middleware\SubstituteBindings::class,
],

Step 2: Setup Model User & Artikel (Ownership Data)

User

Pastikan model User pakai trait HasApiTokens dan relasi ke artikel:

use Laravel\Sanctum\HasApiTokens;

class User extends Authenticatable
{
    use HasApiTokens, Notifiable;
    // ...

    public function articles() {
        return $this->hasMany(Article::class);
    }
}

Artikel

php artisan make:model Article -m

Edit migration:

public function up()
{
    Schema::create('articles', function (Blueprint $table) {
        $table->id();
        $table->string('title');
        $table->text('content');
        $table->foreignId('user_id')->constrained()->cascadeOnDelete();
        $table->timestamps();
    });
}

Jalankan migrasi:

php artisan migrate

Di model Article.php:

protected $fillable = ['title', 'content', 'user_id'];

public function user() {
    return $this->belongsTo(User::class);
}

Step 3: Auth Controller (Register, Login, Logout)

php artisan make:controller Api/AuthController

Contoh fungsi register, login, logout:

public function register(Request $request) {
    $validated = $request->validate([
        'name' => 'required',
        'email' => 'required|email|unique:users',
        'password' => 'required|min:6',
    ]);
    $user = User::create([
        'name' => $validated['name'],
        'email' => $validated['email'],
        'password' => bcrypt($validated['password']),
    ]);
    $token = $user->createToken('api-token')->plainTextToken;
    return response()->json(['user' => $user, 'token' => $token], 201);
}

public function login(Request $request) {
    $credentials = $request->only('email', 'password');
    if (!auth()->attempt($credentials)) {
        return response()->json(['message' => 'Unauthorized'], 401);
    }
    $user = auth()->user();
    $user->tokens()->delete();
    $token = $user->createToken('api-token')->plainTextToken;
    return response()->json(['user' => $user, 'token' => $token]);
}

public function logout(Request $request) {
    $request->user()->currentAccessToken()->delete();
    return response()->json(['message' => 'Logged out']);
}

Step 4: Article Controller (CRUD)

php artisan make:controller Api/ArticleController --resource

Contoh fungsi CRUD:

public function index() {
    return Article::all();
}


public function store(Request $request) {
    $validated = $request->validate([
        'title' => 'required',
        'content' => 'required',
    ]);
    // Ownership: artikel milik user login
    $article = $request->user()->articles()->create($validated);
    return response()->json($article, 201);
}

public function show(Request $request, $id) {
    $article = Article::findOrFail($id);
    // Authorization: hanya pemilik yang boleh akses
    if ($article->user_id !== $request->user()->id) {
        abort(403, 'Unauthorized');
    }
    return $article;
}

public function update(Request $request, $id) {
    $article = Article::findOrFail($id);
    if ($article->user_id !== $request->user()->id) {
        abort(403, 'Unauthorized');
    }
    $validated = $request->validate([
        'title' => 'required',
        'content' => 'required',
    ]);
    $article->update($validated);
    return response()->json($article);
}

public function destroy(Request $request, $id) {
    $article = Article::findOrFail($id);
    if ($article->user_id !== $request->user()->id) {
        abort(403, 'Unauthorized');
    }
    $article->delete();
    return response()->json(null, 204);
}

Step 5: Route API

Edit routes/api.php:

use App\Http\Controllers\Api\AuthController;
use App\Http\Controllers\Api\ArticleController;

Route::post('register', [AuthController::class, 'register']);
Route::post('login', [AuthController::class, 'login']);

Route::middleware('auth:sanctum')->group(function() {
    Route::post('logout', [AuthController::class, 'logout']);
    Route::apiResource('articles', ArticleController::class);
});

Step 6: Testing API CRUD dengan Postman

Method	Endpoint	Fungsi
GET	/api/articles	List semua artikel
POST	/api/articles	Simpan artikel baru
GET	/api/articles/{id}	Detail artikel
PUT	/api/articles/{id}	Update artikel
DELETE	/api/articles/{id}	Hapus artikel

Jangan lupa kirim token di header:

Authorization: Bearer {token}

Contoh Response JSON

{
    "id": 1,
    "title": "Belajar Laravel API",
    "content": "Laravel API itu powerful...",
    "user_id": 1,
    "created_at": "2026-01-11"
}

Kenapa API Ini Aman?

Dengan Sanctum + auth:sanctum, API ini tidak bisa diakses tanpa token. Setiap request divalidasi berdasarkan user yang login, dan hanya pemilik data yang bisa mengakses/mengubah artikelnya sendiri.

Kalau Mau Dipakai di Frontend

React: simpan token di localStorage, kirim di header Authorization setiap request
Axios: gunakan interceptor untuk otomatis attach token
Jangan expose token di public repo!

Error Handling & Status Code

201 Created: Data berhasil dibuat
200 OK: Data berhasil diambil/diupdate
204 No Content: Data dihapus
401 Unauthorized: Token salah/expired
404 Not Found: Data tidak ditemukan
422 Unprocessable Entity: Validasi gagal

Common Mistake Pemula

Lupa migrate/publish Sanctum
Lupa middleware auth:sanctum
Token tidak dikirim di header
Lupa set Accept: application/json
Salah endpoint (POST login, bukan GET)
Salah group route (harus di dalam middleware)

Next Step

API Resource (response lebih rapi)
Pagination & filtering
Role & permission
Testing dengan Thunder Client

🚀 Yuk Diskusi & Share!

Kalau kamu stuck di step tertentu, tulis di komentar ya! Share juga pengalaman kamu bikin API CRUD Laravel, atau request topik lanjutan (API Resource, pagination, dsb).

Referensi:

Laravel API Authentication dengan Sanctum

Muhammad Dhiyaul Atha — Sun, 11 Jan 2026 14:50:53 +0000

"Pernah nggak, API kamu bisa diakses siapa saja tanpa login? Atau frontend sudah jadi, tapi bingung gimana cara login ke backend Laravel? Di sinilah Laravel Sanctum jadi solusi autentikasi API yang simpel dan powerful."

Kenapa Perlu Autentikasi API?

Melindungi data dari akses sembarangan
Wajib untuk aplikasi SPA, mobile, dan public API
User harus login untuk akses data pribadi

Cara Kerja Sanctum (Token Based Auth)

Laravel Sanctum menggunakan token-based authentication. Artinya, setelah login, user akan mendapatkan token yang harus dikirim di setiap request API melalui header Authorization. Ini membuat API lebih aman dan mudah diintegrasikan dengan frontend atau mobile app.

Studi Kasus: API Artikel dengan Login

Di artikel ini, kita akan membuat API Artikel yang hanya bisa diakses user yang sudah login menggunakan Laravel Sanctum.

Step 1: Install Sanctum

composer require laravel/sanctum
php artisan vendor:publish --provider="Laravel\Sanctum\SanctumServiceProvider"
php artisan migrate

Command ini akan menambahkan tabel personal_access_tokens yang digunakan untuk menyimpan token API user.

Tambahkan middleware Sanctum di app/Http/Kernel.php pada group api:

'api' => [
    \Laravel\Sanctum\Http\Middleware\EnsureFrontendRequestsAreStateful::class,
    'throttle:api',
    \Illuminate\Routing\Middleware\SubstituteBindings::class,
],

Step 2: Setup Model User

Pastikan model User pakai trait HasApiTokens:

use Laravel\Sanctum\HasApiTokens;

class User extends Authenticatable
{
    use HasApiTokens, Notifiable;
    // ...
}

Step 3: Membuat Endpoint Auth (Login, Register, Logout)

Buat controller misal AuthController:

php artisan make:controller Api/AuthController

Contoh fungsi register, login, dan logout:

public function register(Request $request) {
    $validated = $request->validate([
        'name' => 'required',
        'email' => 'required|email|unique:users',
        'password' => 'required|min:6',
    ]);
    $user = User::create([
        'name' => $validated['name'],
        'email' => $validated['email'],
        'password' => bcrypt($validated['password']),
    ]);
    $token = $user->createToken('api-token')->plainTextToken;
    return response()->json(['user' => $user, 'token' => $token], 201);
}


public function login(Request $request) {
    $credentials = $request->only('email', 'password');
    if (!auth()->attempt($credentials)) {
        return response()->json(['message' => 'Unauthorized'], 401);
    }
    $user = auth()->user();
    $user->tokens()->delete(); // hapus token lama, 1 user = 1 token aktif
    $token = $user->createToken('api-token')->plainTextToken;
    return response()->json(['user' => $user, 'token' => $token]);
}


public function logout(Request $request) {
    $request->user()->currentAccessToken()->delete();
    // Logout akan menghapus token aktif sehingga request berikutnya akan ditolak.
    return response()->json(['message' => 'Logged out']);
}

Step 4: Route API Auth & Proteksi Artikel

Edit routes/api.php:

Route::post('register', [AuthController::class, 'register']);
Route::post('login', [AuthController::class, 'login']);

Route::middleware('auth:sanctum')->group(function() {
    Route::post('logout', [AuthController::class, 'logout']);
    Route::apiResource('articles', ArticleController::class);
});

Step 5: Testing API Auth dengan Postman

Register

POST /api/register
Content-Type: application/json
{
  "name": "Atha",
  "email": "atha@mail.com",
  "password": "password123"
}

Login

POST /api/login
Content-Type: application/json
{
  "email": "atha@mail.com",
  "password": "password123"
}

Response:

{
  "user": { "id": 1, "name": "Atha", ... },
  "token": "1|longapitoken..."
}

Akses Artikel (dengan token)

Tambahkan header:

Authorization: Bearer 1|longapitoken...

GET /api/articles

Error Handling & Status Code

201 Created: Register sukses
200 OK: Login sukses, data diambil
401 Unauthorized: Token salah/expired
422 Unprocessable Entity: Validasi gagal

Common Mistake Pemula

Lupa publish/migrate Sanctum
Lupa tambahkan middleware auth:sanctum
Token tidak dikirim di header
Lupa set Accept: application/json
Salah endpoint (POST login, bukan GET)
Salah group route (harus di dalam middleware)

Next Step

Refresh token
Role/permission
API Resource
Testing dengan Thunder Client

🚀 Yuk Diskusi & Share!

Kalau kamu stuck di step tertentu, tulis di komentar ya! Share juga pengalaman kamu pakai Sanctum, atau request topik lanjutan (refresh token, role, dsb).

Referensi:

Belajar API Laravel: Dari Problem ke Solusi!

Muhammad Dhiyaul Atha — Sun, 11 Jan 2026 14:24:47 +0000

"Pernah nggak, frontend React kamu gagal ambil data dari backend Laravel? Atau Postman cuma muter-muter nggak dapet respon? Tenang, kamu nggak sendirian! Banyak pemula Laravel ngalamin hal yang sama. Di sinilah API Laravel jadi penyelamat."

Ketika kamu bikin frontend React dan backend Laravel, tapi data nggak tampil karena API belum siap — itu frustrasi banget. Nah, artikel ini kasih solusi lengkapnya biar kamu nggak pusing lagi!

Kenapa API itu Penting?

API itu jembatan antara frontend dan backend
Wajib untuk Single Page Application (SPA) & mobile app
Tanpa API, data nggak bisa ditampilkan ke user

Contoh API Laravel: CRUD Artikel

Di artikel ini, kita bakal bikin API Artikel (CRUD) pakai Laravel. Simpel, tapi bener-bener kepake buat blog, news, atau project latihan.

Alur Kerja API Laravel

Sebelum ngoding, pahami dulu alurnya:

Client (Postman / Frontend)
→ Request HTTP
→ Route API
→ Controller
→ Model
→ Database
→ Response JSON

Jadi, setiap kali client minta data, request-nya lewat route, diproses controller, ambil data dari model/database, lalu balikin response JSON.

Step 1: Setup Project Laravel

Laravel versi terbaru (misal 10.x)
Pastikan Composer sudah terinstal

composer create-project --prefer-dist laravel/laravel belajar-api

Setting database di .env:

DB_CONNECTION=mysql
DB_HOST=127.0.0.1
DB_PORT=3306
DB_DATABASE=belajar_api
DB_USERNAME=root
DB_PASSWORD=

Step 2: Buat Model & Migration Artikel

Kenapa pakai -m?

-m otomatis bikin migration file, jadi nggak perlu bikin manual.

php artisan make:model Article -m

Edit migration di database/migrations/..._create_articles_table.php:

public function up()
{
    Schema::create('articles', function (Blueprint $table) {
        $table->id();
        $table->string('title');
        $table->text('content');
        $table->timestamps();
    });
}

Jalankan migrasi:

php artisan migrate

Pentingnya `$fillable`

Di model Article.php tambahkan:

protected $fillable = ['title', 'content'];

Kenapa harus diisi?

Kalau tidak diisi, Laravel tidak bisa menyimpan data karena proteksi mass assignment. Ini fitur keamanan agar data yang masuk ke database benar-benar sesuai yang diizinkan.

Step 3: Membuat Controller API Artikel

Bikin controller resource:

php artisan make:controller Api/ArticleController --resource

Penjelasan fungsi-fungsi utama:

index() → Ambil semua artikel dari database, balikin dalam bentuk JSON.
store() → Simpan artikel baru. Biasanya ambil data dari request, validasi, lalu simpan.
show($id) → Ambil detail artikel berdasarkan ID.
update($id) → Ubah data artikel tertentu.
destroy($id) → Hapus artikel.

Contoh implementasi (singkat):

public function index() {
    return Article::all();
}

public function store(Request $request) {
    // Validasi dulu
    $validated = $request->validate([
        'title' => 'required',
        'content' => 'required',
    ]);
    // Simpan data
    $article = Article::create($validated);
    return response()->json($article, 201);
}

public function show($id) {
    return Article::findOrFail($id);
}

public function update(Request $request, $id) {
    $article = Article::findOrFail($id);
    $article->update($request->all());
    return response()->json($article);
}

public function destroy($id) {
    Article::destroy($id);
    return response()->json(null, 204);
}

Step 4: Menambahkan Route API

Edit routes/api.php:

Route::apiResource('articles', App\Http\Controllers\Api\ArticleController::class);

Cara Testing API dengan Postman

Cek endpoint pakai Postman/curl:

Method	Endpoint	Fungsi	Contoh Request	Contoh Response
GET	/api/articles	List semua artikel	-	`[ {...} ]`
POST	/api/articles	Simpan artikel baru	`{ "title": "Belajar Laravel API", "content": "Tutorial lengkap & mudah!" }`	`{ "id": 1, ... }`
GET	/api/articles/{id}	Detail artikel	-	`{ "id": 1, ... }`
PUT	/api/articles/{id}	Update artikel	`{ "title": "Update", "content": "Edit konten" }`	`{ "id": 1, ... }`
DELETE	/api/articles/{id}	Hapus artikel	-	`null`

Contoh Lengkap Request & Response

Request POST:

POST /api/articles
Content-Type: application/json

{
    "title": "Belajar Laravel API",
    "content": "Tutorial lengkap & mudah!"
}

Response 201 Created:

{
    "id": 1,
    "title": "Belajar Laravel API",
    "content": "Tutorial lengkap & mudah!",
    "created_at": "2026-01-10"
}

Request GET:

GET /api/articles/1

Response 200 OK:

{
    "id": 1,
    "title": "Belajar Laravel API",
    "content": "Tutorial lengkap & mudah!",
    "created_at": "2026-01-10"
}

Request PUT:

PUT /api/articles/1
Content-Type: application/json

{
    "title": "Update Judul",
    "content": "Konten sudah diupdate!"
}

Response 200 OK:

{
    "id": 1,
    "title": "Update Judul",
    "content": "Konten sudah diupdate!",
    "created_at": "2026-01-10"
}

Request DELETE:

DELETE /api/articles/1

Response 204 No Content:

null

Error Handling & Status Code di Laravel

Laravel otomatis mengirim status code sesuai aksi:

200 OK: Data berhasil diambil/diupdate
201 Created: Data berhasil dibuat
204 No Content: Data berhasil dihapus
404 Not Found: Data tidak ditemukan
422 Unprocessable Entity: Validasi gagal
500 Internal Server Error: Error server

Contoh error response:

{
    "message": "No query results for model [App\\Models\\Article] 99"
}

Tips: Gunakan findOrFail() untuk otomatis dapat response 404 jika data tidak ditemukan.

Common Mistake Pemula

"Kesalahan umum pemula waktu bikin API Laravel:"

Lupa nambah $fillable di model, jadi data nggak bisa disimpan.
Pakai method GET buat simpan data (harusnya POST).
Nggak validasi input, data jadi berantakan.
Langsung expose semua field tanpa filter.
Salah setup .env (database, port, user/password)
Menjalankan route di web.php bukan di api.php
Lupa restart server setelah ubah konfigurasi

Tips: Selalu cek error di response, pastikan method & field sudah benar, dan cek konfigurasi environment!

Next Step: Level Up API-mu!

Jangan berhenti di CRUD. Coba explore:

Sanctum / Auth: Biar API kamu aman
API Resource: Format response lebih rapi
Pagination: Untuk data banyak
Rate Limiting: Biar nggak di-spam

Tunggu artikel lanjutan ya!

🚀 Yuk Diskusi & Share!

Kalau kamu stuck di step tertentu, tulis di komentar ya! Share juga pengalaman kamu bikin API Laravel, atau request topik lanjutan (autentikasi, API resource, pagination, dll).

Jangan lupa follow & share artikel ini ke teman yang lagi belajar Laravel!

Struktur Ringkas

Masalah yang sering dialami pemula
Apa yang akan dibuat
Alur kerja API Laravel
Setup singkat
CRUD API step by step
Testing API
Kesalahan umum
Next step / lanjutan

Referensi:

Laravel Documentation

IDS/IPS Tool: Open Source Modular Intrusion Detection & Prevention System + Real-time Dashboard

Muhammad Dhiyaul Atha — Fri, 19 Dec 2025 22:33:32 +0000

Keamanan server bukan lagi sekadar pilihan, melainkan keharusan. Di dunia di mana serangan brute force dan port scanning terjadi setiap detik, memiliki sistem pertahanan yang ringan dan adaptif adalah kunci.

Saya mengembangkan IDS-IPS-Tool, sebuah solusi keamanan modular berbasis Python yang dirancang untuk deteksi dini dan pencegahan otomatis. Proyek ini bukan sekadar skrip log, melainkan kerangka kerja (framework) keamanan yang siap pakai.

🚀 Kenapa IDS/IPS Tool?

Banyak solusi enterprise sangat kompleks dan berat. IDS-IPS-Tool hadir dengan pendekatan yang berbeda: Modular, Lightweight, dan Dev-Friendly.

🔥 Fitur Utama

IDS (Intrusion Detection System): Analisis file log secara cerdas menggunakan pola Regex untuk mendeteksi failed login, serangan web, dan anomali lainnya.
IPS (Intrusion Prevention System): Tidak hanya mendeteksi, tapi juga menghentikan. Sistem secara otomatis memblokir IP penyerang.
Multi-Firewall Backend: Mendukung iptables, ufw, dan nftables (firewall standar Linux modern). Sistem dapat mendeteksi backend mana yang tersedia secara otomatis.
Network IDS (Sniffer): Dilengkapi dengan kemampuan sniffing paket jaringan secara real-time (ala Suricata) menggunakan library Scapy.
Modern Dashboard: Visualisasi data yang ditenagai oleh FastAPI dan Chart.js untuk memantau trafik dan serangan tanpa perlu membuka terminal.

🏗️ Tech Stack & Arsitektur

Saya merancang alat ini agar mudah dikembangkan (extensible). Semua logika deteksi dipisahkan dari inti program melalui file konfigurasi JSON.

Backend: FastAPI (Asynchronous & High Performance)
Real-time Log Monitoring: Watchdog API
Network Sniffing: Scapy
Frontend: HTML5, TailwindCSS, & Chart.js

Project Structure:

IDS-IPS-Tool/
├── src/           # Modular logic (IDS, IPS, NetIDS)
├── config.json    # Attack signatures & Firewall settings
├── dashboard_main.py # Web UI Entrypoint
├── netids_main.py # Sniffer Entrypoint
└── requirements.txt

⚡ Instalasi & Penggunaan Cepat

Cukup dengan beberapa langkah, Anda bisa mengamankan server Anda:

Clone & Install:

git clone https://github.com/Bangkah/IDS-IPS-Tool.git
cd IDS-IPS-Tool
pip install -r requirements.txt

Konfigurasi Firewall: Atur backend favorit Anda di config.json (auto, nftables, ufw, atau iptables).
Jalankan Dashboard:

python dashboard_main.py

Buka http://localhost:8000 untuk memantau serangan secara real-time!

💡 Lessons Learned

Dalam membangun proyek ini, saya belajar banyak tentang:

Low-level Networking: Bagaimana menangani paket data tanpa membuat bottleneck pada jaringan.
Firewall Orchestration: Berinteraksi dengan kernel Linux melalui berbagai utilitas firewall secara aman.
UI/UX for Security: Menyajikan data keamanan yang kompleks menjadi visualisasi yang mudah dipahami.

🤝 Mari Berkolaborasi!

Proyek ini sepenuhnya open-source dan saya sangat terbuka untuk kontribusi. Apakah itu menambah pola regex baru, integrasi notifikasi Telegram, atau dukungan firewall lainnya.

⭐ Pantau proyeknya di GitHub: Bangkah/IDS-IPS-Tool

python #cybersecurity #linux #opensource #fastapi #securityengineer

Skip the Boilerplate: Scaffold a Production-Ready Laravel Project in Seconds with Bangkah Starter Kit

Muhammad Dhiyaul Atha — Tue, 16 Dec 2025 19:30:45 +0000

Bangkah CLI scaffolding a production-ready Laravel project with Docker support.

Hello developers 👋

Setting up a production-ready Laravel project often means repeating the same steps: configuring Docker, setting up Nginx, wiring authentication, preparing environment files, and optimizing builds. While all of this is necessary, it quickly becomes a time-consuming and repetitive process—especially when you start new projects often.

That’s exactly why I built Bangkah — a Laravel Starter Kit.

Bangkah is a CLI tool designed to eliminate boilerplate and let you scaffold a fully configured, production-ready Laravel project in seconds.

🤔 Why Bangkah? Solving Setup Fatigue

Bangkah goes far beyond a simple composer create-project. It packages the essential infrastructure needed for modern Laravel applications, so you can focus on building features, not setting up the foundation.

⚙️ Key Features

1️⃣ Zero-Config Docker Integration

Bangkah generates a complete and ready-to-use docker-compose.yml, including:

Nginx — pre-configured to serve your Laravel application
PHP-FPM — running PHP 8.2+ with required extensions
Database — choose between MySQL or PostgreSQL during setup

With this setup, you can go from scaffolding to running your app locally using just one or two Docker commands.

2️⃣ Dual Application Templates

Not every Laravel project is a monolith. Bangkah provides two specialized templates depending on your use case:

🖥️ Web Application Template

Ideal for traditional Laravel web apps:

Authentication scaffolding (Laravel Breeze or UI)
Frontend tooling with Vite
Standard web routes and structure

🔌 API Template

Designed for headless backends, SPAs, and mobile apps:

CORS pre-configured
API-first structure
Ready for versioning
Built-in rate limiting

Generated project structure with Docker, Nginx, and Laravel pre-configured.

3️⃣ Optimized for Speed & Security

Bangkah is built with performance and best practices in mind:

Multi-stage Docker builds for smaller and faster images
Optimized Composer installs for quicker dependency management
Pre-integrated modern UI stacks:
- Tailwind CSS
- Bootstrap

Everything is prepared to be production-friendly from day one.

🚀 Get Started

Explore the source code, read the documentation, and try Bangkah today:

🔗 GitHub Repository
https://github.com/Bangkah/bangkah-launcher

🤝 We Need Your Collaboration

Bangkah is 100% open source and built for the Laravel community. If you’re a Laravel developer, you can help by:

Trying it out — see how much setup time you save
Sharing feedback — ideas and suggestions are always welcome
Contributing — fork the repo and submit a Pull Request

Let’s build a faster and cleaner way to launch Laravel projects together 🚀

Happy Coding! 💻✨

Forem: Muhammad Dhiyaul Atha

I Built a Safety-First Workflow Layer for Pacman (ATHA)

What is ATHA?

Example

Why I Built This

Comparison

Installation

Links

💬 Feedback

My First Attempt at Building a Reasoning AI (ARC Prize 2026)

Getting Started

My First Approach (Baseline)

Code & Repository

First Submission (Kaggle)

Why Start Simple?

Why ARC is Hard

First Submission Result

Key Insight

What’s Next?

💡 Final Thoughts

[Boost]

My First Home Server Using a 12-Year-Old Laptop

My First Home Server Using a 12-Year-Old Laptop

When an Old Laptop Finds Its New Purpose

Turning a 2012 MacBook Pro into My First Personal Server

Why an Old Laptop?

System Choice: Arch Linux on Old Hardware

The Struggles: Nothing Worked Perfectly

The Goal: More Than Just Remote Access

The Breakthrough Moment

What I Can Do Now

Final Thoughts

Saya Membuat CLI Tool Jadwal Shalat dan Merilisnya ke Arch Linux AUR

Latar Belakang

Apa Itu jadwal-shalat?

Fitur Utama

Contoh Output

Instalasi via Arch Linux AUR

Instalasi Manual

Cara Kerja Tool Ini

Fokus pada Reliability

Integrasi dengan Arch Linux Packaging

Roadmap ke Depan

Kenapa Saya Membuat Project Ini?

Open Source dan Kontribusi

Penutup

Building Sentinel AI: A Cybersecurity CLI Powered by Copilot

From Copilot Experiment to Production-Ready CLI: Building Sentinel AI

The Idea

How GitHub Copilot Accelerated Development

Architecture Overview

Core Features

Network Scanning

Intelligent Risk Analysis

System Risk Report

System Information

Developer Utilities

From Prototype to Production

Modern Python Packaging

CI/CD Pipeline

Trusted Publishing to PyPI

Installation

Challenges and Lessons Learned

1. CI/CD Discipline

2. Production Packaging

3. CLI Design Principles

4. Copilot as a Force Multiplier

Future Plans

Open Source and Availability

Conclusion

Author

Saat Laptop Lama Menemukan Peran Barunya

Mengubah MacBook Pro 2012 Menjadi Server Pribadi (Eksperimen Pertamaku)

Latar Belakang: Kenapa Laptop Lama?

Pilihan Sistem: Arch Linux di Mesin Tua

Kendala: Tidak Semua Berjalan Mulus

Tujuan: Bukan Sekadar Bisa Remote

Progres: Saat SSH Akhirnya Berhasil

Penutup

Membuat API CRUD di Laravel dengan Sanctum (Step by Step)

Pentingnya `$fillable`