Optimizing nazief adriani's stemmer algorithm in detecting indonesian word errors using sastrawi
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Published:
Nov 8, 2023
Keywords:
Indonesian language, Nazief Adriani's algorithm, Sastrawi, Stemming, Word errors
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Computer Science
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Abstract
The study aimed to enhance the performance of Nazief Adriani's Stemmer Algorithm for detecting word errors in Indonesian texts by utilizing the Sastrawi stemmer. The evaluation utilized a dataset containing Indonesian sentences from a specific source, consisting of 27,704 words. The processing time comparison between the two stemmer algorithms, Nazief Adriani and Sastrawi, is presented in the results. Each algorithm underwent three trials, and it was evident that Sastrawi demonstrated significantly faster processing times, averaging around 2.3254 seconds, while Nazief Adriani averaged approximately 301.7509 seconds. Additionally, the word error count detected by each algorithm in their respective trials is also presented. Nazief Adriani detected 3048 word errors in each trial, whereas Sastrawi detected an average of 1629 word errors. To provide a visual representation of the word error detection comparison, a graphical representation highlighted Sastrawi's superior performance in efficiently identifying word errors in Indonesian texts
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How to Cite
Rosidin, M. ., Gustafi, M. F. . and Pratiwi, S. A. . (2023) “Optimizing nazief adriani’s stemmer algorithm in detecting indonesian word errors using sastrawi”, Jurnal Mantik, 7(3), pp. 1733-1742. doi: 10.35335/mantik.v7i3.4020.
References
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Razmi, N. A., Zamri, M. Z., Ghazalli, S. S. S., & Seman, N. (2021). Visualizing stemming techniques on online news articles text analytics. Bulletin of Electrical Engineering and Informatics, 10(1), 365–365. https://doi.org/10.11591/eei.v10i1.2504
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Rosidin, M., Fadlil, A., & Yudhana, A. (2019). Sistem Kelas Kata Berimbuhan Menggunakan Algoritma Porter Stemmer Sebagai Pembelajaran Bahasa Indonesia. Telematika, 16(1), 11–17.
Rosidin, M., Sulistyo, W. Y., Setyaputri, K. E., & Supriyanto, J. (2022). Rancang Bangun Sistem Informasi Pendataan Beasiswa PTMA Berbasis Web Menggunakan Metode Waterfall. Jurnal Riset Teknologi Informasi Dan Komputer (JURISTIK), 2(1), 7–11. https://doi.org/10.53863/juristik.v2i1.474
Sadanand, V. S., Guruvyas, K. R. R., Patil, P. P., Acharya, J. J., & Suryakanth, S. G. (2022). An automated essay evaluation system using natural language processing and sentiment analysis. International Journal of Electrical and Computer Engineering, 12(6), 6585–6593. https://doi.org/10.11591/ijece.v12i6.pp6585-6593
SIMANJUNTAK, M., Panjaitan, J., & Syahputra, S. A. (2021). Using Preprocessing Text Mining With Nazief-Adriani Algorithms Similarity Of Essay Final Exam Semester. Jurnal Mantik, 5(36), 1714–1720. http://www.iocscience.org/ejournal/index.php/mantik/article/view/1544%0Ahttp://www.iocscience.org/ejournal/index.php/mantik/article/download/1544/1329
Virmani, D., & Taneja, S. (2019). A Text Preprocessing Approach for Efficacious Information Retrieval BT - Smart Innovations in Communication and Computational Sciences (B. K. Panigrahi, M. C. Trivedi, K. K. Mishra, S. Tiwari, & P. K. Singh (eds.); pp. 13–22). Springer Singapore.
Yudhana, A., Fadlil, A., & Rosidin, M. (2019). Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm. IJACSA) International Journal of Advanced Computer Science and Applications, 10(12). https://doi.org/10.14569/IJACSA.2019.0101231
Hidayatullah, S. N., & Suyanto. (2019). Developing an adaptive language model for Bahasa Indonesia. International Journal of Advanced Computer Science and Applications, 10(1), 488–492. https://doi.org/10.14569/IJACSA.2019.0100163
Ibrohim, M. O., & Budi, I. (2019). Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter. 46–57. https://doi.org/10.18653/v1/w19-3506
Isa, S. M., Suwandi, R., & Andrean, Y. P. (2019). Optimizing the hyperparameter of feature extraction and machine learning classification algorithms. International Journal of Advanced Computer Science and Applications, 10(3), 69–76. https://doi.org/10.14569/IJACSA.2019.0100309
Islam, M. I. K., Habib, M. T., Rahman, M. S., Rahman, M. R., & Ahmed, F. (2018). A context-sensitive approach to find optimum language model for automatic Bangla spelling correction. International Journal of Advanced Computer Science and Applications, 9(11), 184–191. https://doi.org/10.14569/ijacsa.2018.091126
Javed, M., & Kamal, S. (2018). Normalization of unstructured and informal text in sentiment analysis. International Journal of Advanced Computer Science and Applications, 9(10), 78–85. https://doi.org/10.14569/IJACSA.2018.091011
Khomsah, S., & Aribowo, A. S. (2017). Text-Preprocessing Komentar Youtube Dalam Bahasa Indonesia. Rekayasa Sistem Dan Teknologi Informasi , 1(3), 648–654.
Li, Y., Du, T., Zhu, L., & Qu, S. (2021). An Efficient Minimal Text Segmentation Method for URL Domain Names. Scientific Programming, 2021, 9946729. https://doi.org/10.1155/2021/9946729
Mantik, J., Indra, S., & Situmeang, G. (2021). 2022) 423-430 Accredited. Jurnal Mantik, 6(1), 423–430.
Mantik, J., Saputri, Y. R., & Februariyanti, H. (2022). Sentiment Analysis on Shopee E-Commerce Using the Naïve Bayes Classifier Algorithm. Jurnal Mantik, 6(2), 1349–1357.
Mustikasari, D., Widaningrum, I., Arifin, R., & Putri, W. H. E. (2021). Comparison of Effectiveness of Stemming Algorithms in Indonesian Documents. Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020), 203, 154–158. https://doi.org/10.2991/aer.k.210810.025
Ni’mah, A. T., & Syuhada, F. (2022). Term Weighting Based Indexing Class and Indexing Short Document for Indonesian Thesis Title Classification. Journal of Computer Science and Informatics Engineering (J-Cosine), 6(2), 167–175.
Nova Sabrina , Buku Rina, C. S. (2020). Jurnal Mantik Jurnal Mantik. Mobile-Based National University Online Library Application Design, 3(2), 10–19. http://iocscience.org/ejournal/index.php/mantik/article/view/882/595
Omar, H., Dahab, M., & Kamal, M. (2016). Stemmer Impact on Quranic Mobile Information Retrieval Performance. International Journal of Advanced Computer Science and Applications, 7(12), 135–139. https://doi.org/10.14569/ijacsa.2016.071218
Prihatini, P. M., Putra, I. K. G. D., Giriantari, I. A. D., & Sudarma, M. (2019). Complete agglomerative hierarchy document’s clustering based on fuzzy Luhn’s gibbs latent dirichlet allocation. International Journal of Electrical and Computer Engineering, 9(3), 2103–2111. https://doi.org/10.11591/ijece.v9i3.pp2103-2111
Razmi, N. A., Zamri, M. Z., Ghazalli, S. S. S., & Seman, N. (2021). Visualizing stemming techniques on online news articles text analytics. Bulletin of Electrical Engineering and Informatics, 10(1), 365–365. https://doi.org/10.11591/eei.v10i1.2504
Resyanto, F., Sibaroni, Y., & Romadhony, A. (2019). Choosing The Most Optimum Text Preprocessing Method for Sentiment Analysis: Case:iPhone Tweets. 2019 Fourth International Conference on Informatics and Computing (ICIC), 1–5. https://doi.org/10.1109/ICIC47613.2019.8985943
Rizki, A. S., Tjahyanto, A., & Trialih, R. (2019). Comparison of stemming algorithms on Indonesian text processing. Telkomnika (Telecommunication Computing Electronics and Control), 17(1), 95–102. https://doi.org/10.12928/TELKOMNIKA.v17i1.10183
Rosid, M. A., Fitrani, A. S., Astutik, I. R. I., Mulloh, N. I., & Gozali, H. A. (2020). Improving Text Preprocessing for Student Complaint Document Classification Using Sastrawi. IOP Conference Series: Materials Science and Engineering, 874(1). https://doi.org/10.1088/1757-899X/874/1/012017
Rosidin, M., Fadlil, A., & Yudhana, A. (2019). Sistem Kelas Kata Berimbuhan Menggunakan Algoritma Porter Stemmer Sebagai Pembelajaran Bahasa Indonesia. Telematika, 16(1), 11–17.
Rosidin, M., Sulistyo, W. Y., Setyaputri, K. E., & Supriyanto, J. (2022). Rancang Bangun Sistem Informasi Pendataan Beasiswa PTMA Berbasis Web Menggunakan Metode Waterfall. Jurnal Riset Teknologi Informasi Dan Komputer (JURISTIK), 2(1), 7–11. https://doi.org/10.53863/juristik.v2i1.474
Sadanand, V. S., Guruvyas, K. R. R., Patil, P. P., Acharya, J. J., & Suryakanth, S. G. (2022). An automated essay evaluation system using natural language processing and sentiment analysis. International Journal of Electrical and Computer Engineering, 12(6), 6585–6593. https://doi.org/10.11591/ijece.v12i6.pp6585-6593
SIMANJUNTAK, M., Panjaitan, J., & Syahputra, S. A. (2021). Using Preprocessing Text Mining With Nazief-Adriani Algorithms Similarity Of Essay Final Exam Semester. Jurnal Mantik, 5(36), 1714–1720. http://www.iocscience.org/ejournal/index.php/mantik/article/view/1544%0Ahttp://www.iocscience.org/ejournal/index.php/mantik/article/download/1544/1329
Virmani, D., & Taneja, S. (2019). A Text Preprocessing Approach for Efficacious Information Retrieval BT - Smart Innovations in Communication and Computational Sciences (B. K. Panigrahi, M. C. Trivedi, K. K. Mishra, S. Tiwari, & P. K. Singh (eds.); pp. 13–22). Springer Singapore.
Yudhana, A., Fadlil, A., & Rosidin, M. (2019). Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm. IJACSA) International Journal of Advanced Computer Science and Applications, 10(12). https://doi.org/10.14569/IJACSA.2019.0101231
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