STEMMING IN MADURESE LANGUAGE USING NAZIEF AND ADRIANI ALGORITHM

Moh Ashari; Danang Arbian Sulistyo; Fadhli Almu’iini Ahda

doi:10.52436/1.jutif.2024.5.4.2012

Moh Ashari Informatics Engineering, Faculty of Technology and Design, Asia Institut of Technology and Business Malang, Indonesia
Danang Arbian Sulistyo Informatics Engineering, Faculty of Technology and Design, Asia Institut of Technology and Business Malang, Indonesia
Fadhli Almu’iini Ahda Informatics Engineering, Faculty of Technology and Design, Asia Institut of Technology and Business Malang, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.4.2012

Keywords: Bahasa Madura, Morfologi, Nazief & Adriani, NLP, Stemming

Abstract

Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island in particular. However, the use of Madurese is declining compared to other regional languages. This is partly due to a sense of prestige and difficulty in learning it. As a result, the future of Madurese as one of the regional languages in Indonesia is increasingly threatened by the decline in its use. In addition, academic literature and scientific publications in Madurese are difficult to find in public and academic libraries, so previous research on Madurese stemming is still very little and needs to be developed further. Therefore, this research aims to find the base word of Madurese language using Nazief & Adriani algorithm based on Madurese language morphology. The Nazief & Adriani method in previous studies has good performance. Stemming can also be developed into a Madurese language translator application into other languages. This research uses 650 words in the form of datasets, consisting of 500 prefix words and 150 suffix words. The resulting accuracy for the whole is 96.61% with 628 correct words, the prefix has 95.6% accuracy, and the suffix has 100% accuracy. Overstemming was found in 22 prefix words and no words experienced Understemming.

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References

F. A. Ahda, A. P. Wibawa, D. Dwi Prasetya, and D. Arbian Sulistyo, “Comparison of Adam Optimization and RMS prop in Minangkabau-Indonesian Bidirectional Translation with Neural Machine Translation,” JOIV Int. J. Inform. Vis., vol. 8, no. 1, p. 231, Mar. 2024, doi: 10.62527/joiv.8.1.1818.

I. Irwiandi and M. Norman, “Proses Morfologis pada Bahasa Madura: Studi pada Mahasiswa Madura di Universitas Trunojoyo,” AIJER Algazali Int. J. Educ. Res., vol. 5, no. 1, pp. 68–75, Oct. 2022, doi: 10.59638/aijer.v5i1.329.

R. Maulidi, “STEMMER UNTUK BAHASA MADURA DENGAN MODIFIKASI METODE ENHANCED CONFIX STRIPPING STEMMER,” . ISSN., 2016.

Indri Tri Julianto, D. Kurniadi, and B. B. Balilo Jr, “ENHANCING SENTIMENT ANALYSIS WITH CHATBOTS: A COMPARATIVE STUDY OF TEXT PRE-PROCESSING,” J. Tek. Inform. Jutif, vol. 4, no. 6, pp. 1419–1430, Dec. 2023, doi: 10.52436/1.jutif.2023.4.6.1448.

V. Amrizal, A. Munandar, and A.- Arini, “IDENTIFIKASI MATAN HADITS MENGGUNAKAN NATURAL LANGUAGE PROCESSING DAN ALGORITMA KNUTH MORRIS PRATT BERBASIS WEB,” J. CoreIT J. Has. Penelit. Ilmu Komput. Dan Teknol. Inf., vol. 5, no. 2, p. 56, Dec. 2019, doi: 10.24014/coreit.v5i2.8477.

S. Tuhpatussania, E. Utami, and A. D. Hartanto, “COMPARISON OF PORTERS STEMMING ALGORITHM AND NAZIEF & ADRIANI’S STEMMING ALGORITHM IN DETERMINING INDONESIAN LANGUAGE LEARNING MODULES,” J. Pilar Nusa Mandiri, vol. 18, no. 2, pp. 203–210, Sep. 2022, doi: 10.33480/pilar.v18i2.3940.

S. B. Rossi Hersianie, “ANALISA MODIFIKASI ALGORITMA STEMMING UNTUK KASUS OVERSTEMMING,” TEKNOKOM, vol. 3, no. 2, pp. 23–28, Dec. 2020, doi: 10.31943/teknokom.v3i2.51.

I. M. A. Agastya, “PENGARUH STEMMER BAHASA INDONESIA TERHADAP PEFORMA ANALISIS SENTIMEN TERJEMAHAN ULASAN FILM,” J. Tekno Kompak, vol. 12, no. 1, p. 18, Feb. 2018, doi: 10.33365/jtk.v12i1.70.

A. F. Aji et al., “One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Dublin, Ireland: Association for Computational Linguistics, 2022, pp. 7226–7249. doi: 10.18653/v1/2022.acl-long.500.

D. A. Sulistyo, “LSTM-Based Machine Translation for Madurese-Indonesian,” J. Appl. Data Sci., vol. 4, no. 3, pp. 189–199, Sep. 2023, doi: 10.47738/jads.v4i3.113.

I Putu Satwika, S.Kom., M. Kom. and Helmy Syahk Alam, “ALGORITMA STEMMING DALAM BAHASA BALI MENGGUNAKAN PENDEKATAN N-GRAM,” Smart Techno Smart Technol. Inform. Technopreneurship, vol. 2, no. 2, pp. 55–63, Sep. 2020, doi: 10.59356/smart-techno.v2i2.22.

F. H. Rachman, N. Ifada, S. Wahyuni, G. D. Ramadani, and A. Pawitra, “ModifiedECS (mECS) Algorithm for Madurese-Indonesian Rule-Based Machine Translation,” in 2022 International Conference of Science and Information Technology in Smart Administration (ICSINTESA), Denpasar, Bali, Indonesia: IEEE, Nov. 2022, pp. 51–56. doi: 10.1109/ICSINTESA56431.2022.10041470.

W. Hidayat, E. Utami, and A. D. Hartanto, “Effect of Stemming Nazief & Adriani on the Ratcliff/Obershelp algorithm in identifying level of similarity between slang and formal words,” in 2020 3rd International Conference on Information and Communications Technology (ICOIACT), Yogyakarta, Indonesia: IEEE, Nov. 2020, pp. 22–27. doi: 10.1109/ICOIACT50329.2020.9331973.

S. Firman Sodiq, W. Desena, and A. Wibowo, “Penerapan Algoritma Stemming Nazief & Adriani Pada Proses Klasterisasi Berita Berdasarkan Tematik Pada Laman (Web) Direktorat Jenderal HAM Menggunakan Rapidminer,” Syntax J. Inform., vol. 11, no. 02, pp. 10–21, Nov. 2022, doi: 10.35706/syji.v11i02.7192.

I. P. M. Wirayasa, I. M. A. Wirawan, and I. M. A. Pradnyana, “ALGORITMA BASTAL: ADAPTASI ALGORITMA NAZIEF & ADRIANI UNTUK STEMMING TEKS BAHASA BALI,” J. Nas. Pendidik. Tek. Inform. JANAPATI, vol. 8, no. 1, p. 60, Jun. 2019, doi: 10.23887/janapati.v8i1.13500.

M. Fauziyah, “JURUSAN TEKNIK INFORMATIKA FAKULTAS SAINS DAN TEKNOLOGI UNIVERSITAS ISLAM NEGERI MAULANA MALIK IBRAHIM MALANG 2019”.

M. Anjani and H. Nurramdhani, “COMPARISON PERFORMANCE OF WORD2VEC, GLOVE, FASTTEXT USING SUPPORT VECTOR MACHINE METHOD FOR SENTIMENT ANALYSIS”.

A. Prasidhatama and K. M. Suryaningrum, “PERBANDINGAN ALGORITMA NAZIEF & ADRIANI DENGAN ALGORITMA IDRIS UNTUK PENCARIAN KATA DASAR,” J. Teknol. Dan Manaj. Inform., vol. 4, no. 1, Jan. 2018, doi: 10.26905/jtmi.v4i1.1773.

M. A. Nq, L. P. Manik, and D. Widiyatmoko, “Stemming Javanese: Another Adaptation of the Nazief-Adriani Algorithm,” in 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia: IEEE, Dec. 2020, pp. 627–631. doi: 10.1109/ISRITI51436.2020.9315420.

G. Septian, A. Susanto, and G. F. Shidik, “Indonesian news classification based on NaBaNA,” in 2017 International Seminar on Application for Technology of Information and Communication (iSemantic), Semarang: IEEE, Oct. 2017, pp. 175–180. doi: 10.1109/ISEMANTIC.2017.8251865.

E. Lindrawati, E. Utami, and A. Yaqin, “Comparison of Modified Nazief&Adriani and Modified Enhanced Confix Stripping algorithms for Madurese Language Stemming,” INTENSIF J. Ilm. Penelit. Dan Penerapan Teknol. Sist. Inf., vol. 7, no. 2, pp. 276–289, Aug. 2023, doi: 10.29407/intensif.v7i2.20103.

A. P. Wibawa, F. A. Dwiyanto, I. A. E. Zaeni, R. K. Nurrohman, and A. Afandi, “Stemming javanese affix words using nazief and adriani modifications,” J. Inform., vol. 14, no. 1, p. 36, Jan. 2020, doi: 10.26555/jifo.v14i1.a17106.