Algoritma clustering untuk mempartisi n observasi ke dalam k kelompok terdekat berdasarkan centroid.
Pelajari sintaks di bawah, pahami alur eksekusi logika interpreter Python, dan uji secara langsung di Code Lab Skillance Academy.
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<style>
body {
font-family: 'Fira Code', Consolas, Monaco, monospace;
background: #0f172a;
color: #f8fafc;
padding: 20px;
margin: 0;
line-height: 1.6;
}
.header {
background: #1e293b;
padding: 10px 16px;
border-radius: 8px 8px 0 0;
border-bottom: 2px solid #334155;
display: flex;
align-items: center;
gap: 8px;
font-size: 13px;
color: #94a3b8;
}
.dot { width: 12px; height: 12px; border-radius: 50%; display: inline-block; }
.dot-red { background: #ef4444; }
.dot-yellow { background: #eab308; }
.dot-green { background: #22c55e; }
.code-box {
background: #1e293b;
padding: 18px 20px;
border-bottom: 1px dashed #334155;
color: #38bdf8;
font-size: 14px;
white-space: pre-wrap;
}
.keyword { color: #f43f5e; font-weight: bold; }
.comment { color: #64748b; font-style: italic; }
.string { color: #4ade80; }
.number { color: #fca311; }
.output-box {
background: #020617;
padding: 18px 20px;
border-radius: 0 0 8px 8px;
color: #e2e8f0;
font-size: 13px;
}
.prompt { color: #fca311; font-weight: bold; }
</style>
</head>
<body>
<div class="header">
<span class="dot dot-red"></span>
<span class="dot dot-yellow"></span>
<span class="dot dot-green"></span>
<span style="margin-left: 8px; font-weight: bold; color: #38bdf8;">K-means - Skillance Python 3.12</span>
</div>
<div class="code-box">
<span class="comment"># Skrip Python - Skillance Academy Indonesia</span>
from sklearn.cluster import KMeans
print('K-Means Centroid Terbentuk')
</div>
<div class="output-box">
<div style="color: #64748b; margin-bottom: 6px;">[Terminal Output] > python main.py</div>
<div style="color: #4ade80; font-weight: bold;">K-Means Centroid Terbentuk</div>
</div>
</body>
</html>Uji skrip Python untuk topik K-means di atas dan amati hasil eksekusi terminalnya secara instan.