ANALISIS PERBANDINGAN KINERJA ALGORITMA STEMMING NAZIEF-ADRIANI DAN IN-IDRIS DALAM PENGOLAHAN TEKS BAHASA INDONESIA

Muhammad Iqbal, Ema Utami, Anggit Dwi Hartanto

Abstract


Stemming merupakan salah satu tahap penting dalam pemrosesan bahasa alami (Natural Language Processing/NLP) untuk mengubah kata berim-buhan menjadi bentuk dasarnya. Penelitian ini membandingkan dua algoritma stemming populer dalam Bahasa Indonesia, yaitu Nazief-Adriani yang berbasis kamus dan In-Idris yang berbasis aturan. Evaluasi dilakukan terhadap tiga jenis dokumen dengan karakteristik gaya bahasa berbeda untuk mengukur kinerja masing-masing algoritma berdasarkan tiga parameter: akurasi, durasi pemrosesan, dan Root Mean Square Er-ror (RMSE). Hasil menunjukkan bahwa algoritma In-Idris memiliki tingkat akurasi lebih tinggi (rata-rata 86%) dan RMSE lebih rendah (0.13) dibandingkan Nazief-Adriani (75,3% dan 0.24), sehingga lebih stabil dan akurat dalam mengidentifikasi bentuk dasar kata. Sementara itu, Nazief-Adriani menunjukkan keunggulan dalam efisiensi waktu pemrosesan. Temuan ini menegaskan pentingnya pemilihan algoritma yang disesuaikan dengan kebutuhan spesifik aplikasi NLP, serta mem-buka peluang pengembangan pendekatan hibrida untuk hasil yang lebih optimal.

Keywords


Stemming, Nazief-Adriani, In-Idris, NLP, Bahasa Indonesia

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References


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DOI: https://doi.org/10.29100/jipi.v11i1.7723

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JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
ISSN 2540-8984
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