Cara Memilih Domain Name yang SEO Friendly dan Strategi Branding yang Kuat di Tahun 2026

import requests
from bs4 import BeautifulSoup
import re

def analyze_competitor_domains(keywords):
    domains = []

    for keyword in keywords:
        # Search Google untuk top 10 results
        search_url = f"https://www.google.com/search?q={keyword}&num=10"
        headers = {'User-Agent': 'Mozilla/5.0'}

        response = requests.get(search_url, headers=headers)
        soup = BeautifulSoup(response.content, 'html.parser')

        # Extract domain patterns
        for result in soup.find_all('div', class_='g'):
            url_element = result.find('a')
            if url_element and 'href' in url_element.attrs:
                domain = re.findall(r'https?://([^/]+)', url_element['href'])
                if domain:
                    domains.append(domain[0])

    return list(set(domains))

# Analyze domain patterns
keywords = ['web development', 'digital marketing', 'SEO services']
competitor_domains = analyze_competitor_domains(keywords)
print(f"Top competitor domains: {competitor_domains}")

# Check keyword density dalam domain
echo "webdevelopmentindonesia.com" | tr '[:upper:]' '[:lower:]' | \
  grep -o -w "web\|development\|indonesia" | sort | uniq -c | \
  awk '{print $2 ": " $1 " (" ($1*100)/NF "%)"}'

import random
import itertools
from wordfreq import zipf_frequency

def generate_seo_domains(base_keywords, modifiers, tlds):
    domains = []

    # Combine keywords dengan modifiers
    for keyword in base_keywords:
        for modifier in modifiers:
            combined = f"{keyword}{modifier}"
            if zipf_frequency(combined, 'en') > 3.0:  # Check naturalness
                for tld in tlds:
                    domains.append(f"{combined}.{tld}")

    # Generate brandable variations
    for keyword in base_keywords:
        variations = [
            keyword.capitalize(),
            keyword + 'ify',
            'get' + keyword,
            keyword + 'hub',
            keyword + 'pro'
        ]

        for variation in variations:
            for tld in ['.com', '.io', '.co']:
                domains.append(f"{variation.lower()}.{tld}")

    return domains

# Usage example
base_keywords = ['tech', 'digital', 'smart']
modifiers = ['solutions', 'pro', 'hub', 'lab']
tlds = ['com', 'io', 'co', 'tech']

domain_suggestions = generate_seo_domains(base_keywords, modifiers, tlds)
print("AI-generated domain suggestions:")
for domain in domain_suggestions[:10]:
    print(f"  - {domain}")

[Brand Element] + [Descriptor] + [TLD]

Examples:
- TechNova Solutions (.com)
- DigitalForge Pro (.io)
- SmartLabs AI (.ai)

const brandabilityScore = {
    memorability: 25,    // How easily remembered
    pronounceability: 20, // How easy to pronounce
    length: 15,         // Shorter is better (6-15 chars ideal)
    uniqueness: 20,      // How distinct from competitors
    extensibility: 20   // Potential for product/service expansion
};

function calculateDomainScore(domain) {
    let score = 0;

    // Memorability test
    score += domain.length <= 10 ? brandabilityScore.memorability :
             domain.length <= 15 ? brandabilityScore.memorability * 0.7 : 0;

    // Pronounceability test
    const pronounceable = /^[a-zA-Z]+$/.test(domain);
    score += pronounceable ? brandabilityScore.pronounceability : 0;

    // Length scoring
    if (domain.length <= 6) score += brandabilityScore.length;
    else if (domain.length <= 10) score += brandabilityScore.length * 0.8;
    else if (domain.length <= 15) score += brandabilityScore.length * 0.5;

    return Math.min(100, score);
}

import whois
import dns.resolver
import concurrent.futures
from datetime import datetime

class DomainChecker:
    def __init__(self):
        self.available_domains = []
        self.taken_domains = []

    def check_domain_availability(self, domain):
        try:
            w = whois.whois(domain)
            # Check jika domain available
            if w.status is None:
                return {'domain': domain, 'available': True, 'reason': 'Available'}
            else:
                expiry_date = w.expiration_date[0] if isinstance(w.expiration_date, list) else w.expiration_date
                return {
                    'domain': domain,
                    'available': False,
                    'expiry': expiry_date,
                    'registrar': w.registrar
                }
        except Exception as e:
            return {'domain': domain, 'available': True, 'reason': str(e)}

    def bulk_domain_check(self, domains):
        with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
            results = list(executor.map(self.check_domain_availability, domains))

        available = [r for r in results if r['available']]
        taken = [r for r in results if not r['available']]

        return {'available': available, 'taken': taken}

# Usage
checker = DomainChecker()
test_domains = ['techsolutions.com', 'digitalpro.io', 'smarthub.co']
results = checker.bulk_domain_check(test_domains)

Domain Value = (Keyword Value × Traffic Score) + Brand Value + Market Premium

# Geographic targeting dengan subdirectory
server {
    listen 443 ssl;
    server_name yourdomain.com;

    # Hreflang implementation
    location ~ ^/(id|en|us)/ {
        # Language/region specific content
        try_files $uri $uri/ /index.php?$query_string;
    }
}

# Geographic targeting dengan subdomain
server {
    listen 443 ssl;
    server_name id.yourdomain.com;

    # Indonesia specific configuration
    root /var/www/id;
    add_header "Content-Language" "id-ID";
}

#!/bin/bash
# Domain security monitoring script

DOMAIN="yourdomain.com"
EXPECTED_NS="ns1.yourhost.com ns2.yourhost.com"

# Check nameserver consistency
CURRENT_NS=$(dig +short NS $DOMAIN | tr '\n' ' ')
if [[ "$CURRENT_NS" != "$EXPECTED_NS" ]]; then
    echo "ALERT: Nameserver change detected for $DOMAIN"
    echo "Expected: $EXPECTED_NS"
    echo "Current: $CURRENT_NS"
    # Send alert notification
fi

# Check domain expiry
EXPIRY_DATE=$(whois $DOMAIN | grep "Registry Expiry Date" | cut -d: -f2 | xargs)
EXPIRY_EPOCH=$(date -d "$EXPIRY_DATE" +%s)
CURRENT_EPOCH=$(date +%s)
DAYS_UNTIL_EXPIRY=$(( (EXPIRY_EPOCH - CURRENT_EPOCH) / 86400 ))

if [[ $DAYS_UNTIL_EXPIRY -lt 30 ]]; then
    echo "WARNING: Domain $DOMAIN expires in $DAYS_UNTIL_EXPIRY days"
fi

server {
    listen 443 ssl http2;
    server_name yourdomain.com www.yourdomain.com;

    # SSL certificate management
    ssl_certificate /etc/letsencrypt/live/yourdomain.com/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/yourdomain.com/privkey.pem;

    # Modern SSL configuration
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers ECDHE-RSA-AES256-GCM-SHA512:DHE-RSA-AES256-GCM-SHA512:ECDHE-RSA-AES256-GCM-SHA384;
    ssl_prefer_server_ciphers off;

    # HSTS untuk domain security
    add_header Strict-Transport-Security "max-age=31536000; includeSubDomains; preload" always;

    # Redirect www ke non-www
    if ($host = www.yourdomain.com) {
        return 301 https://yourdomain.com$request_uri;
    }
}

import requests
import json
from datetime import datetime
import pandas as pd

class DomainAnalytics:
    def __init__(self, api_key):
        self.api_key = api_key
        self.metrics_history = []

    def get_domain_metrics(self, domain):
        # Simulated API call untuk domain metrics
        # Replace dengan actual API calls ke Moz/Ahrefs/Semrush

        metrics = {
            'date': datetime.now().isoformat(),
            'domain': domain,
            'domain_authority': self._get_da(domain),
            'page_authority': self._get_pa(domain),
            'backlinks_count': self._get_backlinks_count(domain),
            'referring_domains': self._get_referring_domains(domain),
            'organic_traffic': self._get_organic_traffic(domain),
            'keyword_rankings': self._get_keyword_rankings(domain)
        }

        self.metrics_history.append(metrics)
        return metrics

    def generate_report(self):
        df = pd.DataFrame(self.metrics_history)

        # Calculate trends
        trend_analysis = {
            'da_trend': self._calculate_trend(df['domain_authority']),
            'traffic_trend': self._calculate_trend(df['organic_traffic']),
            'backlinks_growth': self._calculate_growth(df['backlinks_count'])
        }

        return {
            'current_metrics': df.iloc[-1].to_dict(),
            'trend_analysis': trend_analysis,
            'recommendations': self._generate_recommendations(df)
        }

# Usage
analytics = DomainAnalytics(api_key="your_api_key")
current_metrics = analytics.get_domain_metrics("yourdomain.com")
report = analytics.generate_report()