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All Journal International Journal of Electrical and Computer Engineering IT JOURNAL RESEARCH AND DEVELOPMENT Dinamisia: Jurnal Pengabdian Kepada Masyarakat INTECOMS: Journal of Information Technology and Computer Science EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Linguistik Komputasional jurnal teknik informatika dan sistem informasi Journal of Data Science and Its Applications Community Education Engagement Journal CONSEN: Indonesian Journal of Community Services and Engagement
Arbi Haza Nasution, Arbi Haza
Universitas Islam Riau
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Mathematics Physics Social Sciences Other

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Journal : International Journal of Electrical and Computer Engineering

 1 
Generating similarity cluster of Indonesian languages with semi-supervised clustering Arbi Haza Nasution; Yohei Murakami; Toru Ishida
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.142 KB) | DOI: 10.11591/ijece.v9i1.pp531-538

Abstract

Lexicostatistic and language similarity clusters are useful for computational linguistic researches that depends on language similarity or cognate recognition. Nevertheless, there are no published lexicostatistic/language similarity cluster of Indonesian ethnic languages available. We formulate an approach of creating language similarity clusters by utilizing ASJP database to generate the language similarity matrix, then generate the hierarchical clusters with complete linkage and mean linkage clustering, and further extract two stable clusters with high language similarities. We introduced an extended k-means clustering semi-supervised learning to evaluate the stability level of the hierarchical stable clusters being grouped together despite of changing the number of cluster. The higher the number of the trial, the more likely we can distinctly find the two hierarchical stable clusters in the generated k-clusters. However, for all five experiments, the stability level of the two hierarchical stable clusters is the highest on 5 clusters. Therefore, we take the 5 clusters as the best clusters of Indonesian ethnic languages. Finally, we plot the generated 5 clusters to a geographical map.
Co-Authors Andrian, Dedek Anggi Hanafiah Arif Lukman Hakim Evizariza Evizariza Febri Loska Hafiza Oktasia Nasution Husnul Kausarian Jerika Mardafora Laksono Trisnantoro Lukman Nul Hakim M. Rizki Fadhilah Nofriyandi Nofriyandi Rafi Muhammad Rizky Wandri Salhazan Nasution Salhazan Nasution Salman Saragih Siti Nurhalimah Syafhendry Syafhendry Syafrinaldi Syafrinaldi Toru Ishida Winda Monika Yohei Murakami Yoze Rizki Yudhi Arta Zafrullah