Akurasi Artificial Intelligence Berbasis NLP dalam Mendeteksi Kesalahan Sintaksis Bahasa Indonesia pada Makalah Akademik
DOI:
https://doi.org/10.30762/narasi.v4i2.9900Keywords:
akurasi deteksi, bahasa Indonesia, kesalahan sintaksis, makalah akademikAbstract
Kesalahan sintaksis dalam makalah akademik mahasiswa merupakan permasalahan yang berulang dan berdampak signifikan terhadap kualitas karya tulis ilmiah. Kehadiran teknologi Artificial Intelligence (AI) berbasis Natural Language Processing (NLP) membuka peluang untuk mendeteksi dan mengoreksi kesalahan tersebut secara otomatis. Penelitian ini bertujuan untuk menganalisis secara sistematis tingkat akurasi sistem AI berbasis NLP dalam mendeteksi kesalahan sintaksis pada makalah akademik berbahasa Indonesia berdasarkan kajian literatur yang komprehensif. Metode yang digunakan dalam penelitian ini ialah analisis isi dan evaluasi komparatif terhadap metrik kinerja berbagai model AI. Hasil penelitian menunjukkan bahwa profil kesalahan sintaksis mahasiswa didominasi oleh tataran kalimat (67,02%), khususnya kalimat tanpa subjek dan predikat serta ketidaklogisan struktur. Model Large Language Model (LLM), seperti GPT-4, mencapai F1-Score sebesar 89,79% dalam deteksi koreksi, sementara model Grammatical Error Correction (GEC) khusus, yaitu SAN-GEC dengan fine-tuning, meraih F1-Score sebesar 71,94% dan BLEU-Score sebesar 78,13%. Secara diagnostik, AI paling andal dalam mendeteksi kesalahan morfologi, dengan tingkat akurasi sebesar 84,4%, tetapi menunjukkan kinerja paling rendah dalam penalaran numerik, yaitu 45,0%. Penelitian ini menyimpulkan bahwa AI berbasis NLP berpotensi besar sebagai asisten penyuntingan akademik, tetapi masih memerlukan pengembangan lebih lanjut, khususnya untuk menangani kompleksitas semantik dan penalaran kontekstual dalam bahasa Indonesia.
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Copyright (c) 2026 Bustomi, Moh. Azhar, Ahsan Arrizqi, Akhmad Darul Qutni, Azmi Fadilah, Dheriel Elbazariel
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