Penerapan Natural Language Processing pada Chatbot Edukasi HIV Berbasis Support Vector Machine dan TF-IDF untuk Remaja
DOI:
https://doi.org/10.29407/y2j6nz73Abstract
Human Immunodeficiency Virus merupakan virus yang menyerang sistem kekebalan tubuh dan menjadi permasalahan kesehatan yang signifikan di kalangan remaja. Kurangnya pemahaman tentang HIV menimbulkan stigma dan perilaku berisiko pada kelompok usia tersebut. Penelitian ini bertujuan mengembangkan sistem chatbot edukasi HIV berbasis Natural Language Processing (NLP) menggunakan metode Support Vector Machine (SVM) dan Term Frequency-Inverse Document Frequency (TF-IDF) sebagai perantara peer educator dan remaja. Dataset terdiri dari 300 pasangan pertanyaan dan jawaban yang dikategorikan ke dalam 10 intent. Sistem menggunakan pipeline preprocessing teks yang mencakup cleaning, case folding, tokenisasi, stopword removal, dan stemming. Cosine Similarity diterapkan sebagai typo handler, sementara forward chaining digunakan pada modul kuesioner penilaian risiko. Evaluasi menggunakan confusion matrix menghasilkan akurasi 84%, precision 0,83, recall 0,84, dan F1-score 0,82. Hasil pengujian menunjukkan sistem berjalan sesuai spesifikasi dan efektif sebagai media edukasi HIV bagi remaja.
Keywords:
Chatbot, Edukasi HIV, Natural Language Processing, Support Vector Machine, TF-IDF##plugins.themes.default.displayStats.downloads##
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