The Addition of Indonesian Prefixes meN- and di- to English Bases: A Corpus-based Study

Abstract

This paper serves as an initial identification of the addition of Indonesian inflectional prefixes meN- and di- to English bases of any word class through a corpus-based study. With the prevalence of English influence in Indonesian native speakers’ linguistic repertoire, particularly within the scientific and computational domain, there emerges a tendency to resort to the original terms in English than those of the Indonesian equivalences. This phenomenon, addressed as leksikalisasi timpang or unequal lexicalization, refers to the use of words in source language to make up for the lack of corresponding lexicalization in target language. This leads to a linguistic innovation to ‘localize’ English words by adding Indonesian inflectional prefixes such as meN- and di-. Out of 1 million sentence size Web corpus obtained from The Leipzig Corpora Collection, this paper is able to yield approximately 489 (0,21%) combinations of meN- + English bases with 2,813 (0,018%) word tokens and 475 (0,20%) combinations of di- + English bases with 2,377 (0,015%) word tokens. Six allomorphs of meN- are also attested, namely meng-, men-, mem-, me-, menge-, and meny-, with meng-, men-, and mem- as the most used allomorphs by word frequency and type. This investigation backs up the hypothesis that the process of word assimilation leads to nasal sound changes. This paper also observes that there are 13 most used typographic forms shared between the combinations of meN- and di- + English bases, and 7 other forms on a very low frequency. The words observed in this paper’s database are then grouped into three semantic clusters based on their use in context: computer-related (CR), non-computer-related (NCR), and both (NCR/CR), where computer-related words are observed to dominate the database. The findings indicate that this linguistic creativity is the outcome of how familiar Indonesians are with English terms than the official equivalences, especially towards technology and computational vocabulary.