Deteksi Komentar Spam Menggunakan Algoritma Naive Bayes Berbasis PHP-ML
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Deteksi komentar spam, php-ml, naive bayes, pembelajaran mesinAbstrak
Komentar spam merupakan permasalahan umum dalam sistem interaksi daring seperti blog, forum, dan e-commerce. Penelitian ini merancang dan mengimplementasikan sistem klasifikasi komentar spam berbasis REST API menggunakan Lumen dan pustaka PHP-ML. Sistem menerima komentar dari client aplikasi melalui endpoint API, lalu mengklasifikasikannya sebagai spam atau bukan (ham) menggunakan algoritma Naive Bayes. Komentar yang diterima juga disimpan ke dalam database MySQL dan dapat dilabeli ulang secara manual untuk mendukung retraining model secara berkala. Proses pembelajaran ulang dilakukan melalui command-line interface untuk memanfaatkan data baru dari basis data maupun dataset eksternal. Hasil pengujian menunjukkan bahwa sistem mampu mengklasifikasikan komentar secara real-time dengan tingkat akurasi yang tinggi, serta menyediakan fleksibilitas pembaruan model tanpa mengganggu layanan utama. Sistem ini dinilai efektif dan adaptif untuk diterapkan pada aplikasi web yang membutuhkan deteksi spam komentar secara otomatis dan berkelanjutan
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