Implementation of Raita Algorithm in Manado-Indonesia Translation Application with Text Suggestion Using Levenshtein Distance Algorithm
Abstract
Abstract. Manado City is one of the multidimensional and multicultural cities, possessing assets that are considered highly potential for development into tourism and development attractions. The current tourism assets being developed by the Manado City government are cultural tourism, as they hold a charm and allure for tourists. Hence, a communication tool in the form of a translation application is necessary for facilitating communication between visiting tourists and the native community of North Sulawesi, even for newcomers who intend to reside in North Sulawesi, given that the Manado language serves as the primary communication tool within the community. This research employs a combination of the Raita algorithm and the Levenshtein distance algorithm in its creation process, along with the confusion matrix method to calculate the accuracy of translation results using the Levenshtein distance algorithm with a text suggestion feature. The research begins by collecting a dataset consisting of Manado language vocabulary and their translations in Indonesia language, sourced from literature studies and original respondents from North Sulawesi, which have been validated by a validator to prevent translation data errors. The subsequent stage involves preprocessing the dataset, converting the entire content of the dataset to lowercase using the case folding process, and removing spaces at the start and end of texts using the trim function. Next, both algorithms are implemented, with the Raita algorithm serving for translation and the Levenshtein distance algorithm providing text suggestions for typing errors during the translation process. The accuracy results derived from the confusion matrix calculations during the translation process of 100 vocabulary words, accounting for typing errors, indicate that the Levenshtein distance algorithm is capable of effectively translating vocabulary accurately and correctly, even in the presence of typing errors, resulting in a high accuracy rate of 94,17%.
Purpose: To determine the implementation of the Levenshtein distance and Raita algorithms in the process of using the Manado-Indonesian translation application, as well as the resulting accuracy level.
Methods/Study design/approach: In this study, a combination of the Raita and Levenshtein distance algorithms is utilized in the translation application system, along with the confusion matrix method to calculate accuracy.
Result/Findings: The accuracy achieved in the translation process using text suggestions from the Levenshtein distance algorithm is 94.17%.
Novelty/Originality/Value: This research demonstrates that the combination of the Raita and Levenshtein distance algorithms yields optimal results in the vocabulary translation process and provides accurate outcomes from the use of effective text suggestions. This is attributed to the fact that nearly all the data used was successfully translated by the system, even in the presence of typographical errors.
References
[2] M. R. K. Damopoli, “Aset Tanah dan Bangunan Pemerintah Daerah Kota Manado,” J. Ilmu Polit., vol. Vol. 9, no. 2, pp. 1–11, 2020, [Online]. Available: https://ejournal.unsrat.ac.id/index.php/politico/article/view/30710
[3] F. Kerebungu, “Pengembangan industri pariwisata budaya dalam meningkatkan pendapatan asli daerah (PAD) kota Manado,” Jurnal Aplikasi Manajemen. pp. 289–295, 2020. [Online]. Available: https://www.jurnaljam.ub.ac.id/index.php/jam/article/view/1880
[4] E. Lapian, A. B. Osmond, and R. E. Saputra, “Recurrent neural network untuk pengenalan ucapan pada dialek Manado,” in e-Proceeding of Engineering, 2018, vol. 5, no. 3, pp. 6436–6443. [Online]. Available: https://core.ac.uk/display/299925133
[5] V. (Universitas S. R. Kamu and I. J. (Universitas S. R. Moniung, “Morfologi bahasa Melayu Manado,” J. Kaji. Linguist., vol. 9, no. 2, pp. 248–253, 2021, doi: 10.35796/kaling.9.2.2021.38945.
[6] N. Marbun, M. Zarlis, D. Hartama, Mesran, and B. J. . Sitompul, “Implementasi algoritma raita pada pencarian katalog alkes,” in Seminar Nasional Sains & Teknologi Informasi (SENSASI), 2019, pp. 520–523. [Online]. Available: http://prosiding.seminar-id.com/index.php/sensasi/article/view/357
[7] C. Charras and T. Lecroq, Handbook of exact string matching algorithms. College Publications, 2004. [Online]. Available: https://www.researchgate.net/publication/220693416 Handbook
[8] V. Sahfitri and I. B. Zarizal, “Approximate string matching untuk pencarian kata dalam kamus bahasa indonesia,” J. Ilm. MATRIK, vol. 24, no. 3, pp. 248–259, 2022.
[9] M. J. Tannga, S. Rahman, and Hasniati, “Analisis perbandingan algoritma levenshtein distance dan jaro winkler untuk aplikasi deteksi plagiarisme dokumen teks,” J. Technol. Res. Inf. Syst. Eng., vol. 4, no. 2, pp. 44–54, 2017, [Online]. Available: https://jurnal.kharisma.ac.id/jtriste/article/view/29
[10] F. Pramono, Didi Rosiyadi, and Windu Gata, “Integrasi n-gram, information gain, particle swarm optimation di naïve bayes untuk optimasi sentimen Google Classroom,” J. Rekayasa Sist. dan Teknol. Informasi) (RESTI ), vol. 3, no. 3, pp. 383–388, 2019, doi: 10.29207/resti.v3i3.1119.
[11] K. Munawaroh and A. Alamsyah, “Performance comparison of SVM, naïve bayes, and KNN algorithms for analysis of public opinion sentiment against COVID-19 vaccination on Twitter,” J. Adv. Inf. Syst. Technol., vol. 4, no. 2, pp. 113–125, 2023, doi: 10.15294/jaist.v4i2.59493.
[12] A. Saputra and F. Noor Hasan, “Analisis sentimen terhadap aplikasi coffee meets bagel dengan algoritma naïve bayes classifier,” SIBATIK J. J. Ilm. Bid. Sos. Ekon. Budaya, Teknol. dan Pendidik., vol. 2, no. 2, pp. 465–474, Jan. 2023, doi: 10.54443/sibatik.v2i2.579.
[13] M. M. Yulianto, R. Arifudin, and A. Alamsyah, “Autocomplete and spell checking levenshtein distance algorithm to getting text suggest error data searching in library,” Sci. J. Informatics, vol. 5, no. 1, p. 75, 2018, doi: 10.15294/sji.v5i1.14148.
[14] A. P. U. Siahaan et al., “Combination of levenshtein distance and rabin-karp to improve the accuracy of document equivalence level,” Int. J. Eng. Technol., vol. 7, no. 2 Special Issue 27, pp. 17–21, 2018, doi: 10.14419/ijet.v7i2.27.12084.
[15] K. Al-khamaiseh and S. AlShagarin, “A survey of string matching algorithms,” Int. J. Eng. Res. Appl., vol. 4, no. 7, pp. 144–156, 2014, [Online]. Available: https://www.researchgate.net/publication/279442892
[16] L. Ariyanti and A. Alamsyah, “C4.5 Algorithm Optimization and Support Vector Machine by Applying Particle Swarm Optimization for Chronic Kidney Disease Diagnosis,” Recursive J. Informatics, vol. 1, no. 1, pp. 18–26, 2023, doi: 10.15294/rji.v1i1.65196.
[17] A. Ridhovan and A. Suharso, “Penerapan metode residual network (Resnet) dalam klasifikasi penyakit pada daun gandum,” J. Ilm. Penelit. dan Pembelajaran Inform. (JIPI ), vol. 7, no. 1, pp. 58–65, 2022, doi: 10.29100/jipi.v7i1.2410.
[18] N. Wakhidah and M. Mudi, “The application of simple additive weighting method in the selection of the islamic competition winners,” J. Adv. Inf. …, vol. 1, no. October, pp. 1–12, 2019, [Online]. Available: https://journal.unnes.ac.id/sju/index.php/jaist/article/view/36497%0Ahttps://journal.unnes.ac.id/sju/index.php/jaist/article/download/36497/15063
