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      "keywords": "Artificial Intelligence, Keamanan siber, Cybersecurity, Deepfake, Phishing, Intrusion\r\nDetection System.",
      "lastmod": "2026-07-10 06:49:32",
      "abstract": "Perkembangan teknologi Artificial Intelligence (AI) menciptakan celah\r\nkeamanan baru yang dieksploitasi untuk serangan siber yang lebih canggih dan\r\nadaptif. Penelitian ini bertujuan menganalisis ancaman keamanan digital akibat\r\npenyalahgunaan AI, mengidentifikasi dampaknya terhadap CIA Triad\r\n(Confidentiality, Integrity, Availability), serta merumuskan strategi mitigasi yang\r\nefektif. Metode penelitian menggunakan pendekatan mixed-method dengan\r\nkombinasi studi literatur sistematis, survei terhadap 45 praktisi keamanan siber dan\r\nprofesional IT, serta eksperimen teknis terkontrol meliputi simulasi AI-powered\r\nphishing, deteksi deepfake menggunakan arsitektur Xception, dan pengujian\r\nIntrusion Detection System (Snort). Hasil penelitian menunjukkan serangan\r\nphishing berbasis AI memiliki tingkat kerapian grammar mendekati email\r\nlegitimate (skor 1.0), meningkatkan kesulitan deteksi hingga 45% dibandingkan\r\nmetode konvensional. Model deteksi deepfake mencapai akurasi 94% dengan\r\narsitektur Xception. Survei menunjukkan praktisi menilai dampak terhadap\r\nkerahasiaan (4.56\/5) dan integritas (4.40\/5) sebagai ancaman paling kritis, namun\r\nefektivitas alat deteksi saat ini hanya dinilai moderat (3.33\/5), mengindikasikan\r\nkesenjangan signifikan. Penelitian merekomendasikan transformasi menuju deteksi\r\ncerdas berbasis Machine Learning, penguatan respons insiden otomatis, dan\r\npenerapan analisis forensik berkelanjutan. Kontribusi penelitian meliputi\r\nidentifikasi spesifik enam bentuk penyalahgunaan AI, analisis dampak kuantitatif\r\nberdasarkan data empiris, dan roadmap implementasi praktis untuk meningkatkan\r\npostur keamanan organisasi menghadapi era ancaman siber berbasis AI."
    }