Design Translation Application from Indonesian to the Nyow Dialect (Pepadun) Based on Android

Main Article Content

Sunardi
Yunan Henryanto

Abstract

Language is a sign to communicate. In the world, there are many languages ​​that characterize the country, for example, the State of Indonesia has various regional languages, one of which is the Nyow Dialect (Pepadun) which is dominantly used by residents in the coastal Lampung area to communicate. The purpose of this research is to design and build an Android-based digital dictionary application that can be used to make it easier to find translated vocabulary either in Indonesian or in the Nyow Dialect (Pepadun) so that it can be used in general so as to provide convenience for the wearer. The method used in this thesis is the prototyping method. Based on the test results on the Android-based Indonesian-Now Dialect (Pepadun) application, it can be seen and can conclude several things as follows; The search system designed is able to display words in the database more quickly and equivalently, the search process is carried out by an implicit system where the words to be searched will be processed based on an array that matches the user input string, and system design with Xamarin in the Visual Studio 2017 application package. as an android programming language toll in making applications, it is right because of the ease in the application development process.

Article Details

How to Cite
Sunardi, & Henryanto, Y. (2022). Design Translation Application from Indonesian to the Nyow Dialect (Pepadun) Based on Android. International Journal Software Engineering and Computer Science (IJSECS), 2(1), 18–25. https://doi.org/10.35870/ijsecs.v2i1.762
Section
Articles
Author Biographies

Sunardi, PT. Epsilon

Research Division, PT. Epsilon

Yunan Henryanto, Jhonson Coorporation

Research Division, Jhonson Coorporation

References

Weaver, K.A. and Starner, T., 2011, October. We need to communicate! helping hearing parents of deaf children learn american sign language. In The proceedings of the 13th international ACM SIGACCESS Conference on Computers and Accessibility (pp. 91-98). DOI: https://doi.org/10.1145/2049536.2049554.

Putri, N.W., 2018. Pergeseran bahasa daerah Lampung pada masyarakat kota Bandar Lampung. Jurnal Penelitian Humaniora, 19(2), pp.77-86. DOI: https://doi.org/10.20961/prasasti.v3i1.16550.

Mahendra, Y., Apriza, B. and Rohmani, R., 2022. Analisis Penggunaan Bahasa Ibu dalam Proses Pembelajaran dan Pergaulan Lingkungan Siswa. Jurnal Basicedu, 6(1), pp.700-708. DOI: https://doi.org/10.31004/basicedu.v6i1.2017.

Rich, C., Ponsler, B., Holroyd, A. and Sidner, C.L., 2010, March. Recognizing engagement in human-robot interaction. In 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 375-382). IEEE. DOI: https://doi.org/10.1109/HRI.2010.5453163.

Afifah, N., Santoso, T.B. and Yuliana, M., 2010. Pembuatan Kamus Elektronik Kalimat Bahasa Indonesia dan Bahasa Jawa untuk Aplikasi Mobile Menggunakan Interpolation Search. EEPIS Final Project.

Listyorini, T., 2013. Perancangan mobile learning mata kuliah sistem operasi berbasis android. Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, 3(1), pp.25-30. DOI: https://doi.org/10.24176/simet.v3i1.85.

Godwin-Jones, R., 2011. Mobile apps for language learning. Language learning & technology, 15(2), pp.2-11.

Poornima, C., Dhanalakshmi, V., Anand, K.M. and Soman, K.P., 2011. Rule based sentence simplification for english to tamil machine translation system. International Journal of Computer Applications, 25(8), pp.38-42. DOI: https://doi.org/10.5120/3050-4147.

Sghaier, M.A. and Zrigui, M., 2020. Rule-based machine translation from tunisian dialect to modern standard arabic. Procedia Computer Science, 176, pp.310-319. DOI: https://doi.org/10.1016/j.procs.2020.08.033.

Pratama, I.P.D. and Muliantara, A., 2012. Perancangan dan Implementasi Sistem Penerjemah Teks Bahasa Inggris ke Bahasa Bali Dengan Menggunakan Pendekatan Berbasis Aturan (Rule Based). Jurnal Ilmu Komputer, 5(1), pp.47-54.

Shirvi, N.N. and Panchal, M.H., 2014. Translation of english algorithm in C program using syntax directed translation schema.

Kuhn, T., 2014. A survey and classification of controlled natural languages. Computational linguistics, 40(1), pp.121-170. DOI: https://doi.org/10.1162/COLI_a_00168.

Berger, J. and Packard, G., 2022. Using natural language processing to understand people and culture. American Psychologist, 77(4), p.525.

Tenney, I., Xia, P., Chen, B., Wang, A., Poliak, A., McCoy, R.T., Kim, N., Van Durme, B., Bowman, S.R., Das, D. and Pavlick, E., 2019. What do you learn from context? probing for sentence structure in contextualized word representations. arXiv preprint arXiv:1905.06316. DOI: https://doi.org/10.48550/arXiv.1905.06316.

Richards, J.C. and Schmidt, R.W., 2013. Longman dictionary of language teaching and applied linguistics. Routledge.

Arrasyid, A.N. and Said, M.S., 2016. Aplikasi Kamus Bahasa Daerah Tolaki Berbasis Android. Simtek: jurnal sistem informasi dan teknik komputer, 1(1), pp.62-68. DOI: https://doi.org/10.51876/simtek.v1i1.9.

Wedgwood, H. and Atkinson, J.C., 1872. A dictionary of English etymology. Trübner & Company.

Norri, J., 2016. Dictionary of medical vocabulary in English, 1375–1550: body parts, sicknesses, instruments, and medicinal preparations. Routledge.

Lehmann, W.P., 1986. A Gothic etymological dictionary. Brill.