Halo, saya Hello, I am

Adi Rizky Pratama

Saya seorang I am a

Dosen Teknik Informatika di UBP Karawang sekaligus Programmer Freelance. Menggabungkan riset akademis di bidang AI & Machine Learning dengan pengembangan solusi teknologi nyata untuk industri. Lecturer of Informatics Engineering at UBP Karawang and a Freelance Programmer. Combining academic research in AI & Machine Learning with the development of real-world technology solutions for industry.

6+
Publikasi Publications
50+
Sitasi Citations
10+
Proyek Projects
Dosen & Peneliti Lecturer & Researcher
Full-Stack Dev Full-Stack Dev
AI / ML AI / ML
Geser untuk efek 3D Drag for 3D effect
Adi Rizky Pratama

Akademisi yang Melek Industri Industry-Savvy Academician

Sebagai dosen di Program Studi Teknik Informatika Universitas Buana Perjuangan Karawang, saya mengajar dan meneliti di bidang kecerdasan buatan, pengolahan citra, dan pengembangan aplikasi. Di sisi lain, pengalaman sebagai programmer freelance memungkinkan saya menjembatani teori dan praktik — menghadirkan solusi teknologi yang didasari riset ilmiah yang kuat. As a lecturer in the Informatics Engineering Study Program at Universitas Buana Perjuangan Karawang, I teach and conduct research in artificial intelligence, image processing, and application development. On the other hand, my experience as a freelance programmer allows me to bridge theory and practice — delivering technology solutions built on robust scientific research.

Menjabat sebagai Kepala Pusat Data dan Informasi (PUSDATIN) UBP Karawang, saya terbiasa memimpin proyek digitalisasi skala besar dan berkolaborasi lintas tim. Serving as the Head of the Center for Data and Information (PUSDATIN) at UBP Karawang, I am accustomed to leading large-scale digitalization projects and collaborating across teams.

Dosen Tetap Full-time Lecturer

Teknik Informatika, UBP Karawang Informatics Engineering, UBP Karawang

Riset AI & ML AI & ML Research

CNN, LSTM, k-NN, OCR

Kepala PUSDATIN Head of PUSDATIN

Digitalisasi & Data Center Digitalization & Data Center

Freelance Dev Freelance Dev

Web & Mobile Applications Web & Mobile Applications

Apa yang Bisa Saya Bantu? How Can I Help You?

Menggabungkan keahlian akademis dan pengalaman industri untuk memberikan solusi terbaik. Combining academic expertise and industry experience to deliver the best solutions.

Software Development

Pengembangan aplikasi web & mobile custom sesuai kebutuhan bisnis Anda. Dari landing page hingga sistem enterprise. Custom web & mobile application development tailored to your business needs. From landing pages to enterprise systems.

IT Consulting

Konsultasi arsitektur sistem, pemilihan teknologi, transformasi digital, dan optimasi infrastruktur IT. Consulting on system architecture, technology stack selection, digital transformation, and IT infrastructure optimization.

Corporate Training

Pelatihan pemrograman, data science, dan AI untuk tim korporat maupun institusi pendidikan. Programming, data science, and AI training for corporate teams and educational institutions.

Research Collaboration

Kolaborasi riset di bidang machine learning, computer vision, dan data mining untuk publikasi ilmiah. Research collaboration in machine learning, computer vision, and data mining for scientific publications.

Tech Stack yang Dikuasai Mastered Tech Stack

HTML5
CSS3
JavaScript
Bootstrap
PHP
Laravel
Node.js
Python
TensorFlow
Keras
MySQL
PostgreSQL
Git & GitHub

Tri Dharma Perguruan Tinggi Three Pillars of Higher Education

Pengajaran, penelitian, dan pengabdian masyarakat sebagai fondasi kontribusi ilmiah. Teaching, research, and community service as the foundation of scientific contribution.

Mata Kuliah yang Diampu Courses Taught

Pemrograman Web Web Programming
Kecerdasan Buatan Artificial Intelligence
Machine Learning Machine Learning
Pengolahan Citra Digital Digital Image Processing
Basis Data Database Systems
Pemrograman Mobile Mobile Programming

Pengabdian Masyarakat Community Service

Digitalisasi UMKM melalui implementasi e-learning, QRIS, dan sistem informasi untuk pelaku usaha mikro di Karawang. Digitalization of MSMEs through the implementation of e-learning, QRIS, and information systems for micro-businesses in Karawang.

Highlight Publikasi Riset Research Publication Highlights

1

Penggunaan media pembelajaran Wordwall untuk meningkatkan minat dan motivasi belajar siswa The use of Wordwall learning media to improve students' interest and learning motivation

Zahro, N. A. Q., & Pratama, A. R.

50+ Sitasi 50+ Citations Jurnal Journal
2

Perbandingan Algoritma Apriori Dan FP-Growth Terhadap Market Basket Analysis Comparison of Apriori and FP-Growth Algorithms for Market Basket Analysis

Fathurrahman, M., Pratama, A. R., & Al-Mudzakir, T.

Data Mining Jurnal Journal
3

Implementasi CNN Untuk Klasifikasi Citra Kemasan Kardus Defect dan No Defect CNN Implementation for Defect and No Defect Cardboard Box Image Classification

Antoni, A., Rohana, T., & Pratama, A. R.

Computer Vision CNN

Proyek & Hasil Karya Projects & Creative Works

Koleksi proyek dari dunia akademik, freelance, dan open source. A collection of projects from academic, freelance, and open-source fields.

Memuat proyek... Loading projects...

Pengalaman & Pendidikan Experience & Education

Perjalanan karir di dunia akademik dan industri teknologi. Career journey in the academic world and technology industry.

Akademik Academic 2018 — Sekarang 2018 — Present

Dosen Tetap Full-time Lecturer

Universitas Buana Perjuangan Karawang

Mengajar mata kuliah Pemrograman Web, AI, Machine Learning, dan membimbing riset mahasiswa di Program Studi Teknik Informatika. Teaching Web Programming, AI, Machine Learning, and supervising student research in the Informatics Engineering Study Program.

Freelance Freelance 2019 — Sekarang 2019 — Present

Freelance Web Programmer Freelance Web Programmer

Berbagai Klien & Proyek Various Clients & Projects

Mengembangkan aplikasi web dan mobile untuk klien dari berbagai industri. Spesialisasi di PHP/Laravel, JavaScript, dan Python. Developing web and mobile applications for clients across various industries. Specializing in PHP/Laravel, JavaScript, and Python.

Akademik Academic 2018 — Sekarang 2018 — Present

Kepala PUSDATIN Head of PUSDATIN

UBP Karawang

Memimpin Pusat Data dan Informasi universitas. Mengelola infrastruktur IT, sistem informasi akademik, dan digitalisasi kampus. Leading the university's Center for Data and Information. Managing IT infrastructure, academic information systems, and campus digitalization.

Pengabdian Service 2021 — Sekarang 2021 — Present

Digitalisasi UMKM MSME Digitalization

Karawang & Sekitarnya Karawang & Surrounding Areas

Program pengabdian masyarakat: pelatihan IT, implementasi e-learning dan QRIS untuk pelaku usaha mikro. Community service program: IT training, e-learning implementation, and QRIS integration for micro-businesses.

Pendidikan Education 2015 — 2017

S2 — Magister Teknik Informatika Master of Informatics Engineering

Universitas / Institusi University / Institution

Fokus studi pada kecerdasan buatan, pengolahan citra, dan machine learning. Study focus on artificial intelligence, image processing, and machine learning.

Pendidikan Education 2011 — 2015

S1 — Sarjana Teknik Informatika Bachelor of Informatics Engineering

Universitas / Institusi University / Institution

Fondasi keilmuan di bidang pemrograman, basis data, jaringan komputer, dan rekayasa perangkat lunak. Foundational knowledge in programming, databases, computer networks, and software engineering.

Hubungi Saya Contact Me

Ada proyek, kolaborasi riset, atau pertanyaan? Jangan ragu untuk menghubungi. Have a project, research collaboration, or question? Feel free to reach out.

Mari Berkolaborasi! Let's Collaborate!

Saya selalu terbuka untuk peluang kolaborasi, baik di bidang akademik maupun pengembangan software. Silakan hubungi saya melalui platform berikut. I am always open to collaboration opportunities, both in the academic sphere and software development. Please contact me through the platforms below.

Artikel & Edukasi Articles & Education

Berbagi pengetahuan seputar AI, machine learning, web programming, dan riset teknologi. Sharing insights on AI, machine learning, web programming, and tech research.

Rabu, 01 Juli 2026

AutoBlog AI: Multi-Agent and Self-Hosted Blog Automation Solution

AutoBlog AI: Multi-Agent and Self-Hosted Blog Automation Solution

AutoBlog AI: Multi-Agent and Self-Hosted Blog Automation Solution

Ever thought of having a blog that can update itself without the hassle of writing articles, creating images, and publishing every day? AutoBlog AI is here as the answer. This platform combines artificial intelligence with a multi-agent architecture to automatically generate blog content—from ideas, writing, images, to hosting. And most importantly, everything can be run self-hosted, so your data and content remain fully under your control.

What is AutoBlog AI?

Definition and How It Works

AutoBlog AI is an open-source application that uses AI agents (typically based on Large Language Models like GPT, Claude, or Llama) to autonomously create blog posts. The system works in a pipeline:

  1. Topic selection – the agent determines ideas based on keywords, trends, or RSS feeds.
  2. Research & writing – the agent writes a complete article with an SEO-friendly structure.
  3. Image generation – the agent creates illustrations using an AI image generator.
  4. Publication – the article is directly uploaded to the blogging platform (Google Blogger, WordPress, or static site).

The process runs without human intervention, except during initial configuration.

Self-Hosted Security

Data is an asset. With self-hosted, all content, prompts, and generated images are stored on your private server. No data is sent to third parties (except for the LLM API you choose). You can also control access, backups, and security according to your own standards. Suitable for those who care about privacy or have strict data policies.

Key Features of AutoBlog AI

Multi-Agent Content Pipeline

This is what makes AutoBlog AI different from ordinary automation tools. The system uses multiple agents working in parallel:

  • Research Agent – finds references, facts, and current data.
  • Writer Agent – composes article drafts according to the specified template and tone.
  • Editor Agent – checks grammar, SEO, and consistency.
  • Publisher Agent – schedules and sends content to the target platform.

Each agent has a specific task, resulting in cleaner output and minimal errors. You can set the number of posts per day, priority topics, or focus keywords.

Automatic Image Generation & Hosting

Not just text, AutoBlog AI can also automatically generate supporting images (DALL·E, Stable Diffusion, or Midjourney via API). Images are directly hosted in storage buckets (S3, Cloudflare R2, or local) and inserted into articles. As a result, every post has relevant visuals without needing a designer.

Technology Specifications

Backend and Database

  • Backend: Python (FastAPI or Flask) – lightweight and easy to scale.
  • Database: PostgreSQL (to store drafts, schedules, and logs) + Redis (task queue and cache).
  • Queue System: Celery or Dramatiq to run multi-agent tasks asynchronously.
  • LLM Integration: OpenAI, Anthropic, Ollama (local) — choose according to preference.

Frontend and API Integration

  • Frontend: React or Vue.js — dashboard to monitor queues, edit drafts, and manage settings.
  • RESTful API – all functions can be accessed via API, making it easy to integrate with other tools (Zapier, n8n, or custom webhooks).
  • Platform Integration: Google Blogger API, WordPress REST API, Ghost, or static site generator (Hugo, Jekyll) via Git push.

How to Install & Run the Application

Clone Repository and Environment Preparation

Make sure you have Docker and Docker Compose installed (optional) and Python 3.10+.

git clone https://github.com/namauser/autoblog-ai.git
cd autoblog-ai
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Create a .env file with the minimum content:

LLM_API_KEY=sk-xxxx
BLOG_PLATFORM=blogger
BLOGGER_API_KEY=your_blogger_api_key
BLOG_ID=your_blog_id
IMAGE_GENERATOR=stable_diffusion

Google Blogger Configuration and Execution

  1. Obtain Blogger API credentials – open Google Cloud Console, enable Blogger API, and create an API key or OAuth 2.0.
  2. Set up blog template – ensure your blog is ready to receive automated content (responsive template, on-page SEO).
  3. Run the pipeline:
python run_pipeline.py --topics "AI technology, machine learning developments"

Or if using a scheduler (e.g., cron job every 6 hours):

crontab -e
# add line:
0 */6 * * * cd /path/autoblog-ai && venv/bin/python run_pipeline.py --daily-limit 3

After running, the dashboard can be accessed at http://localhost:8000/dashboard. You can monitor progress, edit articles before publishing, or pause the pipeline.


AutoBlog AI is not just an automation tool—it's a system that you can fully customize. From AI models, writing style, to publication schedules. Suitable for bloggers who want to focus on content strategy without getting stuck in daily routines. Install now, and let the AI agents work for you.

This article was written by artificial intelligence (AI) using the model dahono/deepseek-v4-flash via Dahono Labs.

This article was translated by Artificial Intelligence (AI) using dahono/deepseek-v4-flash via Dahono Labs.

AutoBlog AI: Solusi Otomatisasi Blog dengan Multi-Agent dan Self-Hosted

AutoBlog AI: Solusi Otomatisasi Blog dengan Multi-Agent dan Self-Hosted

AutoBlog AI: Solusi Otomatisasi Blog dengan Multi-Agent dan Self-Hosted

Pernah kepikiran punya blog yang bisa update sendiri tanpa harus repot nulis artikel, bikin gambar, dan publish tiap hari? AutoBlog AI hadir sebagai jawabannya. Platform ini menggabungkan kecerdasan buatan dengan arsitektur multi-agent untuk menghasilkan konten blog secara otomatis—dari ide, penulisan, gambar, hingga hosting. Dan yang paling penting, semuanya bisa kamu jalankan secara self-hosted, jadi data dan konten tetap di bawah kendali penuhmu.

Apa itu AutoBlog AI?

Definisi dan Cara Kerja

AutoBlog AI adalah aplikasi open-source yang menggunakan agen AI (biasanya berbasis Large Language Model seperti GPT, Claude, atau Llama) untuk membuat postingan blog secara otonom. Sistem ini bekerja dalam pipeline:

  1. Pemilihan topik – agen menentukan ide berdasarkan kata kunci, tren, atau feed RSS.
  2. Riset & penulisan – agen menulis artikel lengkap dengan struktur SEO-friendly.
  3. Pembuatan gambar – agen menghasilkan ilustrasi menggunakan AI image generator.
  4. Publikasi – artikel langsung diupload ke platform blogging (Google Blogger, WordPress, atau static site).

Prosesnya berjalan tanpa campur tangan manusia, kecuali saat konfigurasi awal.

Keamanan Self-Hosted

Data adalah aset. Dengan self-hosted, semua konten, prompt, dan gambar yang dihasilkan disimpan di server pribadimu. Tidak ada data yang dikirim ke pihak ketiga (kecuali API LLM yang kamu pilih). Kamu juga bisa mengontrol akses, backup, dan keamanan sesuai standar sendiri. Cocok untuk yang peduli privasi atau punya kebijakan data ketat.

Fitur Unggulan AutoBlog AI

Pipeline Konten Berbasis Multi-Agent

Ini yang bikin AutoBlog AI beda dari tool otomatisasi biasa. Sistem menggunakan beberapa agen yang bekerja paralel:

  • Agent Riset – mencari referensi, fakta, dan data terkini.
  • Agent Penulis – menyusun draf artikel sesuai template dan tone yang ditentukan.
  • Agent Editor – memeriksa tata bahasa, SEO, dan konsistensi.
  • Agent Publisher – menjadwalkan dan mengirim konten ke platform target.

Setiap agen punya tugas spesifik, sehingga output lebih rapi dan minim error. Kamu bisa atur jumlah posting per hari, topik prioritas, atau kata kunci fokus.

Pembuatan Gambar & Hosting Otomatis

Nggak cuma teks, AutoBlog AI juga bisa generate gambar pendukung secara otomatis (DALL·E, Stable Diffusion, atau Midjourney via API). Gambar langsung dihosting di bucket penyimpanan (S3, Cloudflare R2, atau local) dan disisipkan ke artikel. Hasilnya, setiap postingan punya visual yang relevan tanpa perlu desainer.

Spesifikasi Teknologi

Backend dan Database

  • Backend: Python (FastAPI atau Flask) – ringan dan mudah di-scale.
  • Database: PostgreSQL (untuk menyimpan draft, jadwal, dan log) + Redis (antrian tugas dan cache).
  • Queue System: Celery atau Dramatiq untuk menjalankan task multi-agent secara asinkron.
  • LLM Integration: OpenAI, Anthropic, Ollama (local) — pilih sesuai preferensi.

Frontend dan Integrasi API

  • Frontend: React atau Vue.js — dashboard untuk memonitor antrian, edit draft, dan manage pengaturan.
  • API RESTful – semua fungsi bisa diakses via API, sehingga mudah diintegrasikan dengan tool lain (Zapier, n8n, atau webhook custom).
  • Integrasi Platform: Google Blogger API, WordPress REST API, Ghost, atau static site generator (Hugo, Jekyll) via Git push.

Cara Instalasi & Menjalankan Aplikasi

Klon Repositori dan Persiapan Lingkungan

Pastikan sudah install Docker dan Docker Compose (opsional) serta Python 3.10+.

git clone https://github.com/namauser/autoblog-ai.git
cd autoblog-ai
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Buat file .env dengan isi minimal:

LLM_API_KEY=sk-xxxx
BLOG_PLATFORM=blogger
BLOGGER_API_KEY=your_blogger_api_key
BLOG_ID=your_blog_id
IMAGE_GENERATOR=stable_diffusion

Konfigurasi Google Blogger dan Eksekusi

  1. Dapatkan kredensial Blogger API – buka Google Cloud Console, aktifkan Blogger API, dan buat API key atau OAuth 2.0.
  2. Atur template blog – pastikan blogmu sudah siap menerima konten otomatis (template responsif, SEO on-page).
  3. Jalankan pipeline:
python run_pipeline.py --topics "teknologi AI, perkembangan machine learning"

Atau kalau pakai scheduler (misal cron job setiap 6 jam):

crontab -e
# tambahkan baris:
0 */6 * * * cd /path/autoblog-ai && venv/bin/python run_pipeline.py --daily-limit 3

Setelah berjalan, dashboard bisa diakses di http://localhost:8000/dashboard. Kamu bisa pantau progress, edit artikel sebelum publish, atau pause pipeline.


AutoBlog AI bukan cuma tool otomatisasi—ini adalah sistem yang bisa kamu kustomisasi total. Mulai dari model AI, gaya penulisan, hingga jadwal publikasi. Cocok untuk blogger yang ingin fokus pada strategi konten tanpa terjebak rutinitas harian. Install sekarang, dan biarkan agen-agen AI yang bekerja untukmu.

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model dahono/deepseek-v4-flash via Dahono Labs.

New Opportunity for AI Developers: Get $250 Free for Model Experiments

New Opportunity for AI Developers: Get $250 Free for Model Experiments

New Opportunity for AI Developers: Get $250 Free for Model Experiments

Tired of bloated API bills when testing various AI models? Or fed up with managing multiple access keys from OpenAI, Anthropic, DeepSeek, and others? Good news: AgentRouter is here with an offer of $250 in free credits for developers willing to try the "one API, many AI" platform.

Introducing AgentRouter

AgentRouter is a platform that consolidates access to a dozen cutting-edge AI models through a single API endpoint. Instead of signing up for each provider separately, you integrate just one key and instantly call GPT-5, Claude, DeepSeek, GLM, and other models without hassle.

This is not just an ordinary proxy. AgentRouter handles routing, rate limiting, and failover automatically. So if one model is busy, your request will be redirected to another equivalent model. Developers can focus solely on application logic.

Benefits & Supported AI Models

  • Access to the latest models: GPT-5, Claude Opus, DeepSeek V3, GLM-4, Llama 3, Mistral Large, and many more. The AgentRouter team continuously adds new models as they are released.
  • One API for everything: No need to store 5–10 different API keys. Just one credential, one request format, one billing point. This saves significant time and reduces code complexity.
  • Competitive pricing: Plus the $250 bonus, you can make hundreds of thousands of trial requests without spending a penny.

How to Get $250 Free Credit

This offer is special for developers who already have an old GitHub account (at least 6 months old). Why? Because AgentRouter wants to attract serious users who understand the AI ecosystem.

Steps:

  1. Visit AgentRouter.org
  2. Click the "Claim $250 Credit" button
  3. Connect your GitHub account (make sure it is older than 6 months and has active public/private repositories)
  4. After verification, $250 in credit will be added directly to your AgentRouter account
  5. Get your API key and start using any supported model

No credit card is required at this stage. Absolutely free.

Conclusion & Call to Action

Opportunities like this are rare. With $250 in free credits, you can test GPT-5 vs Claude's performance, run Chinese fine-tuning experiments via DeepSeek, or compare GLM inference speed—all without worrying about costs.

Claim yours now before the early user quota runs out. Visit AgentRouter.org now, connect your GitHub, and gain access to dozens of AI models in a single API.

This article was written by artificial intelligence (AI) using the dahono/deepseek-v4-flash model via Dahono Labs.

This article was translated by Artificial Intelligence (AI) using dahono/deepseek-v4-flash via Dahono Labs.

Peluang Baru untuk Developer AI: Dapatkan $250 Gratis untuk Eksperimen Model

Peluang Baru untuk Developer AI: Dapatkan $250 Gratis untuk Eksperimen Model

Peluang Baru untuk Developer AI: Dapatkan $250 Gratis untuk Eksperimen Model

Bosan dengan tagihan API yang membengkak saat menguji berbagai model AI? Atau malas repot mengelola banyak kunci akses dari OpenAI, Anthropic, DeepSeek, dan lainnya? Kabar baik: AgentRouter hadir dengan tawaran $250 kredit gratis bagi developer yang mau mencoba platform “satu API, banyak AI”.

Mengenal AgentRouter

AgentRouter adalah platform yang menggabungkan akses ke belasan model AI mutakhir hanya dengan satu endpoint API. Alih-alih mendaftar ke masing-masing penyedia, Anda cukup integrasikan satu kunci dan langsung bisa memanggil GPT-5, Claude, DeepSeek, GLM, dan model lainnya tanpa repot.

Ini bukan sekadar proxy biasa. AgentRouter mengelola routing, rate limiting, dan failover secara otomatis. Jadi jika satu model sedang sibuk, permintaan Anda akan diarahkan ke model lain yang setara. Developer tinggal fokus pada logika aplikasi.

Keuntungan & Model AI yang Didukung

  • Akses ke model terbaru: GPT-5, Claude Opus, DeepSeek V3, GLM-4, Llama 3, Mistral Large, dan masih banyak lagi. Tim AgentRouter terus menambahkan model baru begitu dirilis.
  • Satu API untuk semuanya: Tak perlu lagi menyimpan 5–10 API key berbeda. Cukup satu kredensial, satu format request, satu billing point. Ini sangat menghemat waktu dan mengurangi kompleksitas kode.
  • Harga kompetitif: Ditambah bonus $250, Anda bisa melakukan ratusan ribu permintaan percobaan tanpa keluar biaya sepeser pun.

Cara Mendapatkan $250 Credit Gratis

Tawaran ini spesial untuk developer yang sudah memiliki akun GitHub lama (minimal 6 bulan). Mengapa? Karena AgentRouter ingin menjaring pengguna serius yang paham ekosistem AI.

Langkah-langkah:

  1. Kunjungi AgentRouter.org
  2. Klik tombol “Claim $250 Credit”
  3. Hubungkan akun GitHub Anda (pastikan akun tersebut sudah berumur >6 bulan dan memiliki repositori publik/non-publik yang aktif)
  4. Setelah verifikasi, saldo $250 langsung ditambahkan ke akun AgentRouter Anda
  5. Dapatkan API key dan mulai gunakan model apa pun yang didukung

Tidak ada kartu kredit yang diperlukan pada tahap ini. Benar-benar gratis.

Kesimpulan & Call to Action

Kesempatan seperti ini jarang terulang. Dengan $250 kredit gratis, Anda bisa menguji performa GPT-5 vs Claude, menjalankan eksperimen fine-tuning cap Cina lewat DeepSeek, atau membandingkan kecepatan inference GLM — semua tanpa memikirkan biaya.

Segera klaim sebelum kuota pengguna awal habis. Kunjungi AgentRouter.org sekarang, hubungkan GitHub Anda, dan dapatkan akses ke puluhan model AI dalam satu API.

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model dahono/deepseek-v4-flash via Dahono Labs.

Introduction to lsb_release Command

Introduction to lsb_release Command

Pernah bingung cek versi Linux yang kamu pakai? Apalagi kalau harus bedain Ubuntu 20.04 sama 22.04, atau Debian 10 vs 11. Di sinilah lsb_release jadi andalan.

What is lsb_release?

lsb_release adalah perintah bawaan di distribusi Linux yang mengikuti standar LSB (Linux Standard Base). Fungsinya: menampilkan informasi identitas sistem, mulai dari nama distribusi, versi, hingga kode rilis (seperti “Focal Fossa” untuk Ubuntu 20.04).

Why Use lsb_release for Version Checking?

  • Sederhana: satu baris perintah, hasil langsung keluar.
  • Terstandar: sama di berbagai distro (Ubuntu, Debian, Linux Mint, dll).
  • Cocok untuk scripting: outputnya mudah diparsing, misalnya untuk keperluan otomasi atau troubleshooting.

Step-by-Step Usage of lsb_release -a

Opening the Terminal

Tekan Ctrl + Alt + T di keyboard, atau cari “Terminal” di menu aplikasi. Siap? Lanjut.

Executing the Command

Ketik perintah berikut, lalu tekan Enter:

lsb_release -a

Tunggu beberapa detik, maka informasi akan muncul langsung di layar.


Interpreting the Output

Setelah menjalankan perintah di atas, kamu akan melihat beberapa baris teks. Masing-masing punya arti:

Understanding Each Field

  • Distributor ID: Nama vendor distribusi, misalnya Ubuntu, Debian, atau Linuxmint.
  • Description: Nama lengkap distribusi beserta versinya, contoh Ubuntu 22.04.3 LTS.
  • Release: Nomor versi utama, seperti 22.04.
  • Codename: Nama kode rilis, misalnya jammy (untuk Ubuntu 22.04).

Common Output Examples

Ubuntu 22.04

No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 22.04.3 LTS
Release:        22.04
Codename:       jammy

Debian 11

Distributor ID: Debian
Description:    Debian GNU/Linux 11 (bullseye)
Release:        11
Codename:       bullseye
Kalau muncul pesan “No LSB modules are available”, tenang aja. Itu cuma peringatan, bukan error. Informasi versi tetap keluar.

Alternative Methods and Tips

Using hostnamectl or /etc/os-release

Kalau lsb_release tidak ada—atau kamu ingin opsi lain—bisa pakai cara ini:

hostnamectl (systemd):

hostnamectl

Outputnya akan menampilkan Operating System beserta versinya.

Membaca file /etc/os-release (lebih mentah, tapi andal):

cat /etc/os-release

File ini berisi variabel lingkungan seperti PRETTY_NAME, VERSION_ID, dan ID. Cocok buat scripting.

Troubleshooting lsb_release Not Found

Pesan “command not found” biasanya karena paket lsb-release belum terinstal. Solusi:

  • Debian/Ubuntu: sudo apt install lsb-release
  • Fedora/RHEL: sudo dnf install redhat-lsb-core
  • Arch Linux: sudo pacman -S lsb-release

Setelah terinstal, coba lagi perintah lsb_release -a.


Dengan lsb_release, cek versi Linux jadi cepat dan nggak ribet. Simpan perintah ini di bookmark mentalmu, ya.

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model dahono/deepseek-v4-flash via Dahono Labs.

Selasa, 30 Juni 2026

Cara Cek Versi Ubuntu dengan lsb_release -a (Lengkap)

Pernah butuh tahu versi Ubuntu yang kamu pakai? Entah untuk install aplikasi, cari bantuan di forum, atau sekadar ingin tahu rilis apa yang berjalan di mesinmu. Perintah paling standar dan praktis adalah lsb_release -a.

Mengenal Perintah lsb_release -a

Fungsi lsb_release dalam Sistem Ubuntu

Perintah lsb_release adalah alat resmi untuk menampilkan informasi distribusi Linux yang mengikuti standar LSB (Linux Standard Base). Di Ubuntu, fungsinya sangat jelas: memberikan detail soal versi sistem, kode nama (codename), deskripsi, hingga ID distributor. Semua informasi distro yang kamu butuhkan bisa didapat dari satu perintah ini.

Keunggulan lsb_release -a Dibanding Metode Lain

Kenapa harus pakai lsb_release?

  • Output terstruktur dan mudah dibaca. Hasilnya langsung rapi, tidak perlu parsing file konfigurasi.
  • Standar LSB. Perintah ini ada di hampir semua distribusi berbasis Debian, jadi portabel.
  • Lengkap. Dengan opsi -a, semua informasi distro ditampilkan sekaligus: deskripsi, versi, codename, dan ID.
  • Lebih andal ketimbang membaca file /etc/os-release atau /etc/lsb-release yang terkadang formatnya berbeda-beda antar sistem.

Langkah-Langkah Cek Versi Ubuntu dengan lsb_release -a

Membuka Terminal dan Menjalankan Perintah

Buka terminal lewat menu atau pintasan Ctrl+Alt+T. Ketikkan perintah berikut:

lsb_release -a

Tekan Enter. Tunggu sebentar, output akan muncul.

Contoh Output dan Cara Membacanya

Berikut contoh output dari Ubuntu 22.04 LTS:

Distributor ID: Ubuntu
Description:    Ubuntu 22.04.5 LTS
Release:        22.04
Codename:       jammy

Output terdiri dari empat baris. Cara bacanya simpel: setiap baris berisi label dan nilainya. Description memberi tahu kamu bahwa sistem ini adalah Ubuntu 22.04.5 LTS. Codename-nya jammy.

Interpretasi Detail Output lsb_release -a

Arti Setiap Baris pada Output

Baris Arti
Distributor ID Nama distributor, misalnya Ubuntu.
Description Deskripsi lengkap versi, termasuk titik rilis (point release) dan status LTS jika ada.
Release Nomor rilis utama, contoh 22.04.
Codename Nama kode rilis, seperti jammy, focal, bionic.

Kapan Informasi Ini Dibutuhkan

Informasi ini sangat berguna ketika:

  • Memasang paket atau repositori pihak ketiga yang bergantung pada versi tertentu.
  • Mencari solusi di forum – biasanya mereka akan menanyakan output lsb_release -a terlebih dahulu.
  • Mengecek apakah sistem sudah menggunakan rilis terbaru atau masih versi lama.
  • Menulis dokumentasi atau script yang harus kompatibel dengan banyak versi Ubuntu.

Mengatasi lsb_release Tidak Terinstall

Terkadang di sistem minimal (Docker, server minimal) perintah lsb_release belum tersedia. Tenang, instalasinya mudah.

Menginstall lsb-release Package

Jalankan dua perintah berikut di terminal:

sudo apt update
sudo apt install lsb-release

Setelah selesai, cobaLagi perintah lsb_release -a.

Alternatif Command Cek Versi Ubuntu

Kalau kamu tidak bisa atau tidak ingin menginstall lsb-release, beberapa perintah lain bisa dijadikan alternatif:

  1. cat /etc/os-release – File standar systemd yang berisi informasi distro. Outputnya bisa lebih panjang tapi cukup informatif.
  2. hostnamectl – Perintah dari systemd, selain menampilkan hostname juga menunjukkan versi OS dan kernel.
  3. cat /etc/lsb-release – File khusus LSB, kalau ada. Biasanya isinya mirip dengan output lsb_release.

Contoh penggunaan:

cat /etc/os-release

Atau:

hostnamectl | grep -i ubuntu

Dengan cara-cara di atas, kamu bisa tetap tahu versi Ubuntu bahkan ketika lsb_release belum terpasang. Simpan saja perintah alternatif ini di catatanmu!

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model dahono/deepseek-v4-flash via Dahono Labs.

Why Termius is the Top Choice for Sysadmins

Working as a sysadmin means being ready to manage servers anytime, anywhere. From your office laptop, your phone on the go, to your tablet at home. This is where Termius stands out: one SSH app that works seamlessly on Android, iOS, Windows, macOS, and Linux. No more memorizing hostnames and credentials for each device—automatic cloud-based sync keeps all connection configurations, keys, and snippets the same no matter where you log in. Set it up once, and the rest takes care of itself.

Key Features That Simplify Daily Work

Connection management in Termius isn't just a list of addresses. You can organize servers using groups and tags. For example, a production group, a staging group, or tags like nginx and database. Find a server instantly without mindless scrolling.

Two features that stand out in practice:

  • Port Forwarding – Need to tunnel into a database only accessible from an internal server? Just set up local port forwarding from the Termius interface, without needing to remember the -L syntax.
  • Agent Forwarding – SSH agent forwarding works out-of-the-box, especially useful when hopping from one bastion host to another server. Termius handles key forwarding transparently.

Pros and Cons You Should Know

Pros:

  • Modern and intuitive UI – A clean terminal, tab management, and a built-in dark theme. Great for those migrating from PuTTY's outdated interface.
  • Clipboard sync – Copy text from a server on your laptop, paste it on your phone. Clipboard syncs automatically between devices as long as you're logged into the same account.
  • Extensions and integrations – Termius includes a snippet manager, keychain, and support for SFTP directly from the same window.

Cons:

  • Paid pro features – Multi-device sync, port forwarding, and collaboration features require a subscription. The free version is sufficient for basic single-device use, but if you seriously need cross-platform sync, you'll need to pay.
  • No advanced terminal features – Such as split pane, tmux integration, or session recording. This is more of a modern terminal client, not a full replacement for tools like Konsole or iTerm2 with extreme customization features.

Comparison with Other SSH Clients

Termius vs PuTTY / OpenSSH

PuTTY is free and lightweight, but its interface feels like stepping back into the Windows XP era. No groups, no sync, and port forwarding must be remembered manually. The OpenSSH command line is undeniably powerful, but without a GUI, navigating between sessions is slow. Termius excels in ease of use and cross-platform consistency.

Termius vs Paid Clients (SecureCRT, Royal TS)

SecureCRT has much more mature scripting features, and Royal TS supports many protocols beyond SSH (RDP, VNC). However, they are more expensive and typically licensed per seat. Termius offers ease of use at a more affordable subscription price, and its cloud sync ecosystem is rare among competitors. If your needs revolve around mobility and small team collaboration, Termius feels like a better fit.


Bottom line: Termius isn't the most feature-rich terminal out there, but it's the most practical solution for sysadmins working across multiple devices. If automatic sync and a clean UI are priorities, and you don't mind a monthly fee for pro features, Termius is worth a try.

This article was written by artificial intelligence (AI) using the dahono/deepseek-v4-flash model via Dahono Labs.

This article was translated by Artificial Intelligence (AI) using dahono/deepseek-v4-flash via Dahono Labs.

Adi Rizky Pratama

Dosen Teknik Informatika di UBP Karawang sekaligus Programmer Freelance. Menggabungkan riset akademis di bidang AI & Machine Learning dengan pengembangan solusi teknologi nyata untuk industri.

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