Word Classification in the Online Database of Malay-Arabic Comparable Phrases

Abstract

This paper will present the word classification method in developing a Malay- Arabic corpus online database. Word classification was developed in this model to explain to users about the types of words in the sentences and phrases displayed as the search results of Malay-Arabic comparable sentences. Word classification is a method of describing to users, especially to students who have a problem with identifying word classes, particularly in the Arabic language. Word classes are divided based on three main classes of the Arabic language, namely ism, fi?il and harf. Ism is divided into ism ?alam and ism mushtaq. Ism mushtaq is divided into masdar, ism al-fa?il, ism al-ma?ful, ism al-zaman and ism al-makan. Fi?il is divided into three main components, namely fi?il al-madhi, fi?il al-mudhari’ and fi?il al-amr. While harf is in harf component only. The method of listing each of these word class components is done using a software that separates each sentence component entry based on word class. The development of this database was made by using PHP software, MySQL Database and Linux-based Web Server System. The word class displayed will be in accordance with each phrase or sentence entry inserted, together with the translations. User is only required to enter a keyword in the search box and the system will display the search results of comparable Malay-Arabic phrases or sentences along with the word classes.

Authors and Affiliations

Taj Rijal Muhamad Romli, Md Zahar Othman, Mohd Hilmi Abdullah, Mohd Zawawi Awang Hamat

Keywords

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  • EP ID EP558780
  • DOI 10.6007/IJARPED/v7-i4/4853
  • Views 109
  • Downloads 0

How To Cite

Taj Rijal Muhamad Romli, Md Zahar Othman, Mohd Hilmi Abdullah, Mohd Zawawi Awang Hamat (2018). Word Classification in the Online Database of Malay-Arabic Comparable Phrases. International Journal of Academic Research in Progressive Education and Development, 7(4), 255-266. https://europub.co.uk/articles/-A-558780